Improving treatment plan evaluation with automation.

PubMed

Covington, Elizabeth L; Chen, Xiaoping; Younge, Kelly C; Lee, Choonik; Matuszak, Martha M; Kessler, Marc L; Keranen, Wayne; Acosta, Eduardo; Dougherty, Ashley M; Filpansick, Stephanie E; Moran, Jean M

2016-11-08

The goal of this work is to evaluate the effectiveness of Plan-Checker Tool (PCT) which was created to improve first-time plan quality, reduce patient delays, increase the efficiency of our electronic workflow, and standardize and automate the phys-ics plan review in the treatment planning system (TPS). PCT uses an application programming interface to check and compare data from the TPS and treatment management system (TMS). PCT includes a comprehensive checklist of automated and manual checks that are documented when performed by the user as part of a plan readiness check for treatment. Prior to and during PCT development, errors identified during the physics review and causes of patient treatment start delays were tracked to prioritize which checks should be automated. Nineteen of 33checklist items were automated, with data extracted with PCT. There was a 60% reduction in the number of patient delays in the six months after PCT release. PCT was suc-cessfully implemented for use on all external beam treatment plans in our clinic. While the number of errors found during the physics check did not decrease, automation of checks increased visibility of errors during the physics check, which led to decreased patient delays. The methods used here can be applied to any TMS and TPS that allows queries of the database. © 2016 The Authors.

Stochastic Evolutionary Algorithms for Planning Robot Paths

NASA Technical Reports Server (NTRS)

Fink, Wolfgang; Aghazarian, Hrand; Huntsberger, Terrance; Terrile, Richard

2006-01-01

A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.

Energy aware path planning in complex four dimensional environments

NASA Astrophysics Data System (ADS)

Chakrabarty, Anjan

This dissertation addresses the problem of energy-aware path planning for small autonomous vehicles. While small autonomous vehicles can perform missions that are too risky (or infeasible) for larger vehicles, the missions are limited by the amount of energy that can be carried on board the vehicle. Path planning techniques that either minimize energy consumption or exploit energy available in the environment can thus increase range and endurance. Path planning is complicated by significant spatial (and potentially temporal) variations in the environment. While the main focus is on autonomous aircraft, this research also addresses autonomous ground vehicles. Range and endurance of small unmanned aerial vehicles (UAVs) can be greatly improved by utilizing energy from the atmosphere. Wind can be exploited to minimize energy consumption of a small UAV. But wind, like any other atmospheric component , is a space and time varying phenomenon. To effectively use wind for long range missions, both exploration and exploitation of wind is critical. This research presents a kinematics based tree algorithm which efficiently handles the four dimensional (three spatial and time) path planning problem. The Kinematic Tree algorithm provides a sequence of waypoints, airspeeds, heading and bank angle commands for each segment of the path. The planner is shown to be resolution complete and computationally efficient. Global optimality of the cost function cannot be claimed, as energy is gained from the atmosphere, making the cost function inadmissible. However the Kinematic Tree is shown to be optimal up to resolution if the cost function is admissible. Simulation results show the efficacy of this planning method for a glider in complex real wind data. Simulation results verify that the planner is able to extract energy from the atmosphere enabling long range missions. The Kinematic Tree planning framework, developed to minimize energy consumption of UAVs, is applied for path planning

Planning for Office Automation.

ERIC Educational Resources Information Center

Mick, Colin K.

1983-01-01

Outlines a practical approach to planning for office automation termed the "Focused Process Approach" (the "what" phase, "how" phase, "doing" phase) which is a synthesis of the problem-solving and participatory planning approaches. Thirteen references are provided. (EJS)

The Automated Logistics Element Planning System (ALEPS)

NASA Technical Reports Server (NTRS)

Schwaab, Douglas G.

1991-01-01

The design and functions of ALEPS (Automated Logistics Element Planning System) is a computer system that will automate planning and decision support for Space Station Freedom Logistical Elements (LEs) resupply and return operations. ALEPS provides data management, planning, analysis, monitoring, interfacing, and flight certification for support of LE flight load planning activities. The prototype ALEPS algorithm development is described.

Path planning algorithms for assembly sequence planning. [in robot kinematics

NASA Technical Reports Server (NTRS)

Krishnan, S. S.; Sanderson, Arthur C.

1991-01-01

Planning for manipulation in complex environments often requires reasoning about the geometric and mechanical constraints which are posed by the task. In planning assembly operations, the automatic generation of operations sequences depends on the geometric feasibility of paths which permit parts to be joined into subassemblies. Feasible locations and collision-free paths must be present for part motions, robot and grasping motions, and fixtures. This paper describes an approach to reasoning about the feasibility of straight-line paths among three-dimensional polyhedral parts using an algebra of polyhedral cones. A second method recasts the feasibility conditions as constraints in a nonlinear optimization framework. Both algorithms have been implemented and results are presented.

Robot path planning using a genetic algorithm

NASA Technical Reports Server (NTRS)

Cleghorn, Timothy F.; Baffes, Paul T.; Wang, Liu

1988-01-01

Robot path planning can refer either to a mobile vehicle such as a Mars Rover, or to an end effector on an arm moving through a cluttered workspace. In both instances there may exist many solutions, some of which are better than others, either in terms of distance traversed, energy expended, or joint angle or reach capabilities. A path planning program has been developed based upon a genetic algorithm. This program assumes global knowledge of the terrain or workspace, and provides a family of good paths between the initial and final points. Initially, a set of valid random paths are constructed. Successive generations of valid paths are obtained using one of several possible reproduction strategies similar to those found in biological communities. A fitness function is defined to describe the goodness of the path, in this case including length, slope, and obstacle avoidance considerations. It was found that with some reproduction strategies, the average value of the fitness function improved for successive generations, and that by saving the best paths of each generation, one could quite rapidly obtain a collection of good candidate solutions.

Improving treatment plan evaluation with automation

PubMed Central

Covington, Elizabeth L.; Chen, Xiaoping; Younge, Kelly C.; Lee, Choonik; Matuszak, Martha M.; Kessler, Marc L.; Keranen, Wayne; Acosta, Eduardo; Dougherty, Ashley M.; Filpansick, Stephanie E.

2016-01-01

The goal of this work is to evaluate the effectiveness of Plan‐Checker Tool (PCT) which was created to improve first‐time plan quality, reduce patient delays, increase the efficiency of our electronic workflow, and standardize and automate the physics plan review in the treatment planning system (TPS). PCT uses an application programming interface to check and compare data from the TPS and treatment management system (TMS). PCT includes a comprehensive checklist of automated and manual checks that are documented when performed by the user as part of a plan readiness check for treatment. Prior to and during PCT development, errors identified during the physics review and causes of patient treatment start delays were tracked to prioritize which checks should be automated. Nineteen of 33 checklist items were automated, with data extracted with PCT. There was a 60% reduction in the number of patient delays in the six months after PCT release. PCT was successfully implemented for use on all external beam treatment plans in our clinic. While the number of errors found during the physics check did not decrease, automation of checks increased visibility of errors during the physics check, which led to decreased patient delays. The methods used here can be applied to any TMS and TPS that allows queries of the database. PACS number(s): 87.55.‐x, 87.55.N‐, 87.55.Qr, 87.55.tm, 89.20.Bb PMID:27929478

Mission-directed path planning for planetary rover exploration

NASA Astrophysics Data System (ADS)

Tompkins, Paul

2005-07-01

Robotic rovers uniquely benefit planetary exploration---they enable regional exploration with the precision of in-situ measurements, a combination impossible from an orbiting spacecraft or fixed lander. Mission planning for planetary rover exploration currently utilizes sophisticated software for activity planning and scheduling, but simplified path planning and execution approaches tailored for localized operations to individual targets. This approach is insufficient for the investigation of multiple, regionally distributed targets in a single command cycle. Path planning tailored for this task must consider the impact of large scale terrain on power, speed and regional access; the effect of route timing on resource availability; the limitations of finite resource capacity and other operational constraints on vehicle range and timing; and the mutual influence between traverses and upstream and downstream stationary activities. Encapsulating this reasoning in an efficient autonomous planner would allow a rover to continue operating rationally despite significant deviations from an initial plan. This research presents mission-directed path planning that enables an autonomous, strategic reasoning capability for robotic explorers. Planning operates in a space of position, time and energy. Unlike previous hierarchical approaches, it treats these dimensions simultaneously to enable globally-optimal solutions. The approach calls on a near incremental search algorithm designed for planning and re-planning under global constraints, in spaces of higher than two dimensions. Solutions under this method specify routes that avoid terrain obstacles, optimize the collection and use of rechargable energy, satisfy local and global mission constraints, and account for the time and energy of interleaved mission activities. Furthermore, the approach efficiently re-plans in response to updates in vehicle state and world models, and is well suited to online operation aboard a robot

Bim-Based Indoor Path Planning Considering Obstacles

NASA Astrophysics Data System (ADS)

Xu, M.; Wei, S.; Zlatanova, S.; Zhang, R.

2017-09-01

At present, 87 % of people's activities are in indoor environment; indoor navigation has become a research issue. As the building structures for people's daily life are more and more complex, many obstacles influence humans' moving. Therefore it is essential to provide an accurate and efficient indoor path planning. Nowadays there are many challenges and problems in indoor navigation. Most existing path planning approaches are based on 2D plans, pay more attention to the geometric configuration of indoor space, often ignore rich semantic information of building components, and mostly consider simple indoor layout without taking into account the furniture. Addressing the above shortcomings, this paper uses BIM (IFC) as the input data and concentrates on indoor navigation considering obstacles in the multi-floor buildings. After geometric and semantic information are extracted, 2D and 3D space subdivision methods are adopted to build the indoor navigation network and to realize a path planning that avoids obstacles. The 3D space subdivision is based on triangular prism. The two approaches are verified by the experiments.

Introduction of a computer-based method for automated planning of reduction paths under consideration of simulated muscular forces.

PubMed

Buschbaum, Jan; Fremd, Rainer; Pohlemann, Tim; Kristen, Alexander

2017-08-01

Reduction is a crucial step in the surgical treatment of bone fractures. Finding an optimal path for restoring anatomical alignment is considered technically demanding because collisions as well as high forces caused by surrounding soft tissues can avoid desired reduction movements. The repetition of reduction movements leads to a trial-and-error process which causes a prolonged duration of surgery. By planning an appropriate reduction path-an optimal sequence of target-directed movements-these problems should be overcome. For this purpose, a computer-based method has been developed. Using the example of simple femoral shaft fractures, 3D models are generated out of CT images. A reposition algorithm aligns both fragments by reconstructing their broken edges. According to the criteria of a deduced planning strategy, a modified A*-algorithm searches collision-free route of minimal force from the dislocated into the computed target position. Muscular forces are considered using a musculoskeletal reduction model (OpenSim model), and bone collisions are detected by an appropriate method. Five femoral SYNBONE models were broken into different fracture classification types and were automatically reduced from ten randomly selected displaced positions. Highest mean translational and rotational error for achieving target alignment is [Formula: see text] and [Formula: see text]. Mean value and standard deviation of occurring forces are [Formula: see text] for M. tensor fasciae latae and [Formula: see text] for M. semitendinosus over all trials. These pathways are precise, collision-free, required forces are minimized, and thus regarded as optimal paths. A novel method for planning reduction paths under consideration of collisions and muscular forces is introduced. The results deliver additional knowledge for an appropriate tactical reduction procedure and can provide a basis for further navigated or robotic-assisted developments.

Visually based path-planning by Japanese monkeys.

PubMed

Mushiake, H; Saito, N; Sakamoto, K; Sato, Y; Tanji, J

2001-03-01

To construct an animal model of strategy formation, we designed a maze path-finding task. First, we asked monkeys to capture a goal in the maze by moving a cursor on the screen. Cursor movement was linked to movements of each wrist. When the animals learned the association between cursor movement and wrist movement, we established a start and a goal in the maze, and asked them to find a path between them. We found that the animals took the shortest pathway, rather than approaching the goal randomly. We further found that the animals adopted a strategy of selecting a fixed intermediate point in the visually presented maze to select one of the shortest pathways, suggesting a visually based path planning. To examine their capacity to use that strategy flexibly, we transformed the task by blocking pathways in the maze, providing a problem to solve. The animals then developed a strategy of solving the problem by planning a novel shortest path from the start to the goal and rerouting the path to bypass the obstacle.

Automating Acquisitions: The Planning Process.

ERIC Educational Resources Information Center

Bryant, Bonita

1984-01-01

Account of process followed at large academic library in preparing for automation of acquisition and fund accounting functions highlights planning criteria, local goals, planning process elements (selecting participants, assigning tasks, devising timetable, providing foundations, evaluating systems, determining costs, formulating recommendations).…

A Bat Algorithm with Mutation for UCAV Path Planning

PubMed Central

Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi

2012-01-01

Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models. PMID:23365518

A bat algorithm with mutation for UCAV path planning.

PubMed

Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi

2012-01-01

Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models.

Path Planning Algorithms for Autonomous Border Patrol Vehicles

NASA Astrophysics Data System (ADS)

Lau, George Tin Lam

This thesis presents an online path planning algorithm developed for unmanned vehicles in charge of autonomous border patrol. In this Pursuit-Evasion game, the unmanned vehicle is required to capture multiple trespassers on its own before any of them reach a target safe house where they are safe from capture. The problem formulation is based on Isaacs' Target Guarding problem, but extended to the case of multiple evaders. The proposed path planning method is based on Rapidly-exploring random trees (RRT) and is capable of producing trajectories within several seconds to capture 2 or 3 evaders. Simulations are carried out to demonstrate that the resulting trajectories approach the optimal solution produced by a nonlinear programming-based numerical optimal control solver. Experiments are also conducted on unmanned ground vehicles to show the feasibility of implementing the proposed online path planning algorithm on physical applications.

Planning paths through a spatial hierarchy - Eliminating stair-stepping effects

NASA Technical Reports Server (NTRS)

Slack, Marc G.

1989-01-01

Stair-stepping effects are a result of the loss of spatial continuity resulting from the decomposition of space into a grid. This paper presents a path planning algorithm which eliminates stair-stepping effects induced by the grid-based spatial representation. The algorithm exploits a hierarchical spatial model to efficiently plan paths for a mobile robot operating in dynamic domains. The spatial model and path planning algorithm map to a parallel machine, allowing the system to operate incrementally, thereby accounting for unexpected events in the operating space.

Remote imagery for unmanned ground vehicles: the future of path planning for ground robotics

NASA Astrophysics Data System (ADS)

Frederick, Philip A.; Theisen, Bernard L.; Ward, Derek

2006-10-01

Remote Imagery for Unmanned Ground Vehicles (RIUGV) uses a combination of high-resolution multi-spectral satellite imagery and advanced commercial off-the-self (COTS) object-oriented image processing software to provide automated terrain feature extraction and classification. This information, along with elevation data, infrared imagery, a vehicle mobility model and various meta-data (local weather reports, Zobler Soil map, etc...), is fed into automated path planning software to provide a stand-alone ability to generate rapidly updateable dynamic mobility maps for Manned or Unmanned Ground Vehicles (MGVs or UGVs). These polygon based mobility maps can reside on an individual platform or a tactical network. When new information is available, change files are generated and ingested into existing mobility maps based on user selected criteria. Bandwidth concerns are mitigated by the use of shape files for the representation of the data (e.g. each object in the scene is represented by a shape file and thus can be transmitted individually). User input (desired level of stealth, required time of arrival, etc...) determines the priority in which objects are tagged for updates. This paper will also discuss the planned July 2006 field experiment.

Rotational-path decomposition based recursive planning for spacecraft attitude reorientation

NASA Astrophysics Data System (ADS)

Xu, Rui; Wang, Hui; Xu, Wenming; Cui, Pingyuan; Zhu, Shengying

2018-02-01

The spacecraft reorientation is a common task in many space missions. With multiple pointing constraints, it is greatly difficult to solve the constrained spacecraft reorientation planning problem. To deal with this problem, an efficient rotational-path decomposition based recursive planning (RDRP) method is proposed in this paper. The uniform pointing-constraint-ignored attitude rotation planning process is designed to solve all rotations without considering pointing constraints. Then the whole path is checked node by node. If any pointing constraint is violated, the nearest critical increment approach will be used to generate feasible alternative nodes in the process of rotational-path decomposition. As the planning path of each subdivision may still violate pointing constraints, multiple decomposition is needed and the reorientation planning is designed as a recursive manner. Simulation results demonstrate the effectiveness of the proposed method. The proposed method has been successfully applied in two SPARK microsatellites to solve onboard constrained attitude reorientation planning problem, which were developed by the Shanghai Engineering Center for Microsatellites and launched on 22 December 2016.

Mobile robot dynamic path planning based on improved genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

In dynamic unknown environment, the dynamic path planning of mobile robots is a difficult problem. In this paper, a dynamic path planning method based on genetic algorithm is proposed, and a reward value model is designed to estimate the probability of dynamic obstacles on the path, and the reward value function is applied to the genetic algorithm. Unique coding techniques reduce the computational complexity of the algorithm. The fitness function of the genetic algorithm fully considers three factors: the security of the path, the shortest distance of the path and the reward value of the path. The simulation results show that the proposed genetic algorithm is efficient in all kinds of complex dynamic environments.

A knowledge-based approach to automated planning for hepatocellular carcinoma.

PubMed

Zhang, Yujie; Li, Tingting; Xiao, Han; Ji, Weixing; Guo, Ming; Zeng, Zhaochong; Zhang, Jianying

2018-01-01

To build a knowledge-based model of liver cancer for Auto-Planning, a function in Pinnacle, which is used as an automated inverse intensity modulated radiation therapy (IMRT) planning system. Fifty Tomotherapy patients were enrolled to extract the dose-volume histograms (DVHs) information and construct the protocol for Auto-Planning model. Twenty more patients were chosen additionally to test the model. Manual planning and automatic planning were performed blindly for all twenty test patients with the same machine and treatment planning system. The dose distributions of target and organs at risks (OARs), along with the working time for planning, were evaluated. Statistically significant results showed that automated plans performed better in target conformity index (CI) while mean target dose was 0.5 Gy higher than manual plans. The differences between target homogeneity indexes (HI) of the two methods were not statistically significant. Additionally, the doses of normal liver, left kidney, and small bowel were significantly reduced with automated plan. Particularly, mean dose and V15 of normal liver were 1.4 Gy and 40.5 cc lower with automated plans respectively. Mean doses of left kidney and small bowel were reduced with automated plans by 1.2 Gy and 2.1 Gy respectively. In contrast, working time was also significantly reduced with automated planning. Auto-Planning shows availability and effectiveness in our knowledge-based model for liver cancer. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Interactive multi-objective path planning through a palette-based user interface

NASA Astrophysics Data System (ADS)

Shaikh, Meher T.; Goodrich, Michael A.; Yi, Daqing; Hoehne, Joseph

2016-05-01

n a problem where a human uses supervisory control to manage robot path-planning, there are times when human does the path planning, and if satisfied commits those paths to be executed by the robot, and the robot executes that plan. In planning a path, the robot often uses an optimization algorithm that maximizes or minimizes an objective. When a human is assigned the task of path planning for robot, the human may care about multiple objectives. This work proposes a graphical user interface (GUI) designed for interactive robot path-planning when an operator may prefer one objective over others or care about how multiple objectives are traded off. The GUI represents multiple objectives using the metaphor of an artist's palette. A distinct color is used to represent each objective, and tradeoffs among objectives are balanced in a manner that an artist mixes colors to get the desired shade of color. Thus, human intent is analogous to the artist's shade of color. We call the GUI an "Adverb Palette" where the word "Adverb" represents a specific type of objective for the path, such as the adverbs "quickly" and "safely" in the commands: "travel the path quickly", "make the journey safely". The novel interactive interface provides the user an opportunity to evaluate various alternatives (that tradeoff between different objectives) by allowing her to visualize the instantaneous outcomes that result from her actions on the interface. In addition to assisting analysis of various solutions given by an optimization algorithm, the palette has additional feature of allowing the user to define and visualize her own paths, by means of waypoints (guiding locations) thereby spanning variety for planning. The goal of the Adverb Palette is thus to provide a way for the user and robot to find an acceptable solution even though they use very different representations of the problem. Subjective evaluations suggest that even non-experts in robotics can carry out the planning tasks with a

Research on global path planning based on ant colony optimization for AUV

NASA Astrophysics Data System (ADS)

Wang, Hong-Jian; Xiong, Wei

2009-03-01

Path planning is an important issue for autonomous underwater vehicles (AUVs) traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization (ACO) were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.

Development of a plan for automating integrated circuit processing

NASA Technical Reports Server (NTRS)

1971-01-01

The operations analysis and equipment evaluations pertinent to the design of an automated production facility capable of manufacturing beam-lead CMOS integrated circuits are reported. The overall plan shows approximate cost of major equipment, production rate and performance capability, flexibility, and special maintenance requirements. Direct computer control is compared with supervisory-mode operations. The plan is limited to wafer processing operations from the starting wafer to the finished beam-lead die after separation etching. The work already accomplished in implementing various automation schemes, and the type of equipment which can be found for instant automation are described. The plan is general, so that small shops or large production units can perhaps benefit. Examples of major types of automated processing machines are shown to illustrate the general concepts of automated wafer processing.

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs.

PubMed

Wang, Xiaoliang; Jiang, Peng; Li, Deshi; Sun, Tao

2017-09-19

Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region.

A novel representation for planning 3-D collision-free paths

NASA Technical Reports Server (NTRS)

Bonner, Susan; Kelley, Robert B.

1990-01-01

A new scheme for the representation of objects, the successive spherical approximation (SSA), facilitates the rapid planning of collision-free paths in a dynamic three-dimensional environment. The hierarchical nature of the SSA allows collisions to be determined efficiently while still providing an exact representation of objects. The rapidity with which collisions can be detected, less than 1 sec per environment object per path, makes it possible to use a generate-and-test path-planning strategy driven by human conceptual knowledge to determine collision-free paths in a matter of seconds on a Sun 3/180 computer. A hierarchy of rules, based on the concept of a free space cell, is used to find heuristically satisfying collision-free paths in a structured environment.

UAVSAR Flight-Planning System

NASA Technical Reports Server (NTRS)

2008-01-01

A system of software partly automates planning of a flight of the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) -- a polarimetric synthetic-aperture radar system aboard an unpiloted or minimally piloted airplane. The software constructs a flight plan that specifies not only the intended flight path but also the setup of the radar system at each point along the path.

Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning

PubMed Central

Kok, Kai Yit; Rajendran, Parvathy

2016-01-01

The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost. PMID:26943630

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs

PubMed Central

Jiang, Peng; Li, Deshi; Sun, Tao

2017-01-01

Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region. PMID:28925960

Automated Planning for a Deep Space Communications Station

NASA Technical Reports Server (NTRS)

Estlin, Tara; Fisher, Forest; Mutz, Darren; Chien, Steve

1999-01-01

This paper describes the application of Artificial Intelligence planning techniques to the problem of antenna track plan generation for a NASA Deep Space Communications Station. Me described system enables an antenna communications station to automatically respond to a set of tracking goals by correctly configuring the appropriate hardware and software to provide the requested communication services. To perform this task, the Automated Scheduling and Planning Environment (ASPEN) has been applied to automatically produce antenna trucking plans that are tailored to support a set of input goals. In this paper, we describe the antenna automation problem, the ASPEN planning and scheduling system, how ASPEN is used to generate antenna track plans, the results of several technology demonstrations, and future work utilizing dynamic planning technology.

Dual stage potential field method for robotic path planning

NASA Astrophysics Data System (ADS)

Singh, Pradyumna Kumar; Parida, Pramod Kumar

2018-04-01

Path planning for autonomous mobile robots are the root for all autonomous mobile systems. Various methods are used for optimization of path to be followed by the autonomous mobile robots. Artificial potential field based path planning method is one of the most used methods for the researchers. Various algorithms have been proposed using the potential field approach. But in most of the common problems are encounters while heading towards the goal or target. i.e. local minima problem, zero potential regions problem, complex shaped obstacles problem, target near obstacle problem. In this paper we provide a new algorithm in which two types of potential functions are used one after another. The former one is to use to get the probable points and later one for getting the optimum path. In this algorithm we consider only the static obstacle and goal.

Path Planning Algorithms for the Adaptive Sensor Fleet

NASA Technical Reports Server (NTRS)

Stoneking, Eric; Hosler, Jeff

2005-01-01

The Adaptive Sensor Fleet (ASF) is a general purpose fleet management and planning system being developed by NASA in coordination with NOAA. The current mission of ASF is to provide the capability for autonomous cooperative survey and sampling of dynamic oceanographic phenomena such as current systems and algae blooms. Each ASF vessel is a software model that represents a real world platform that carries a variety of sensors. The OASIS platform will provide the first physical vessel, outfitted with the systems and payloads necessary to execute the oceanographic observations described in this paper. The ASF architecture is being designed for extensibility to accommodate heterogenous fleet elements, and is not limited to using the OASIS platform to acquire data. This paper describes the path planning algorithms developed for the acquisition phase of a typical ASF task. Given a polygonal target region to be surveyed, the region is subdivided according to the number of vessels in the fleet. The subdivision algorithm seeks a solution in which all subregions have equal area and minimum mean radius. Once the subregions are defined, a dynamic programming method is used to find a minimum-time path for each vessel from its initial position to its assigned region. This path plan includes the effects of water currents as well as avoidance of known obstacles. A fleet-level planning algorithm then shuffles the individual vessel assignments to find the overall solution which puts all vessels in their assigned regions in the minimum time. This shuffle algorithm may be described as a process of elimination on the sorted list of permutations of a cost matrix. All these path planning algorithms are facilitated by discretizing the region of interest onto a hexagonal tiling.

UAV path planning using artificial potential field method updated by optimal control theory

NASA Astrophysics Data System (ADS)

Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long

2016-04-01

The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.

Automated planning of tangential breast intensity-modulated radiotherapy using heuristic optimization.

PubMed

Purdie, Thomas G; Dinniwell, Robert E; Letourneau, Daniel; Hill, Christine; Sharpe, Michael B

2011-10-01

To present an automated technique for two-field tangential breast intensity-modulated radiotherapy (IMRT) treatment planning. A total of 158 planned patients with Stage 0, I, and II breast cancer treated using whole-breast IMRT were retrospectively replanned using automated treatment planning tools. The tools developed are integrated into the existing clinical treatment planning system (Pinnacle(3)) and are designed to perform the manual volume delineation, beam placement, and IMRT treatment planning steps carried out by the treatment planning radiation therapist. The automated algorithm, using only the radio-opaque markers placed at CT simulation as inputs, optimizes the tangential beam parameters to geometrically minimize the amount of lung and heart treated while covering the whole-breast volume. The IMRT parameters are optimized according to the automatically delineated whole-breast volume. The mean time to generate a complete treatment plan was 6 min, 50 s ± 1 min 12 s. For the automated plans, 157 of 158 plans (99%) were deemed clinically acceptable, and 138 of 158 plans (87%) were deemed clinically improved or equal to the corresponding clinical plan when reviewed in a randomized, double-blinded study by one experienced breast radiation oncologist. In addition, overall the automated plans were dosimetrically equivalent to the clinical plans when scored for target coverage and lung and heart doses. We have developed robust and efficient automated tools for fully inversed planned tangential breast IMRT planning that can be readily integrated into clinical practice. The tools produce clinically acceptable plans using only the common anatomic landmarks from the CT simulation process as an input. We anticipate the tools will improve patient access to high-quality IMRT treatment by simplifying the planning process and will reduce the effort and cost of incorporating more advanced planning into clinical practice. Crown Copyright © 2011. Published by Elsevier Inc

Path Planning for Robot based on Chaotic Artificial Potential Field Method

NASA Astrophysics Data System (ADS)

Zhang, Cheng

2018-03-01

Robot path planning in unknown environments is one of the hot research topics in the field of robot control. Aiming at the shortcomings of traditional artificial potential field methods, we propose a new path planning for Robot based on chaotic artificial potential field method. The path planning adopts the potential function as the objective function and introduces the robot direction of movement as the control variables, which combines the improved artificial potential field method with chaotic optimization algorithm. Simulations have been carried out and the results demonstrate that the superior practicality and high efficiency of the proposed method.

Robust Path Planning and Feedback Design Under Stochastic Uncertainty

NASA Technical Reports Server (NTRS)

Blackmore, Lars

2008-01-01

Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.

Path Planning Method in Multi-obstacle Marine Environment

NASA Astrophysics Data System (ADS)

Zhang, Jinpeng; Sun, Hanxv

2017-12-01

In this paper, an improved algorithm for particle swarm optimization is proposed for the application of underwater robot in the complex marine environment. Not only did consider to avoid obstacles when path planning, but also considered the current direction and the size effect on the performance of the robot dynamics. The algorithm uses the trunk binary tree structure to construct the path search space and A * heuristic search method is used in the search space to find a evaluation standard path. Then the particle swarm algorithm to optimize the path by adjusting evaluation function, which makes the underwater robot in the current navigation easier to control, and consume less energy.

Planning actions in robot automated operations

NASA Technical Reports Server (NTRS)

Das, A.

1988-01-01

Action planning in robot automated operations requires intelligent task level programming. Invoking intelligence necessiates a typical blackboard based architecture, where, a plan is a vector between the start frame and the goal frame. This vector is composed of partially ordered bases. A partial ordering of bases presents good and bad sides in action planning. Partial ordering demands the use of a temporal data base management system.

Planning paths to multiple targets: memory involvement and planning heuristics in spatial problem solving.

PubMed

Wiener, J M; Ehbauer, N N; Mallot, H A

2009-09-01

For large numbers of targets, path planning is a complex and computationally expensive task. Humans, however, usually solve such tasks quickly and efficiently. We present experiments studying human path planning performance and the cognitive processes and heuristics involved. Twenty-five places were arranged on a regular grid in a large room. Participants were repeatedly asked to solve traveling salesman problems (TSP), i.e., to find the shortest closed loop connecting a start location with multiple target locations. In Experiment 1, we tested whether humans employed the nearest neighbor (NN) strategy when solving the TSP. Results showed that subjects outperform the NN-strategy, suggesting that it is not sufficient to explain human route planning behavior. As a second possible strategy we tested a hierarchical planning heuristic in Experiment 2, demonstrating that participants first plan a coarse route on the region level that is refined during navigation. To test for the relevance of spatial working memory (SWM) and spatial long-term memory (LTM) for planning performance and the planning heuristics applied, we varied the memory demands between conditions in Experiment 2. In one condition the target locations were directly marked, such that no memory was required; a second condition required participants to memorize the target locations during path planning (SWM); in a third condition, additionally, the locations of targets had to retrieved from LTM (SWM and LTM). Results showed that navigation performance decreased with increasing memory demands while the dependence on the hierarchical planning heuristic increased.

Automation and Intensity Modulated Radiation Therapy for Individualized High-Quality Tangent Breast Treatment Plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Purdie, Thomas G., E-mail: Tom.Purdie@rmp.uhn.on.ca; Department of Radiation Oncology, University of Toronto, Toronto, Ontario; Techna Institute, University Health Network, Toronto, Ontario

Purpose: To demonstrate the large-scale clinical implementation and performance of an automated treatment planning methodology for tangential breast intensity modulated radiation therapy (IMRT). Methods and Materials: Automated planning was used to prospectively plan tangential breast IMRT treatment for 1661 patients between June 2009 and November 2012. The automated planning method emulates the manual steps performed by the user during treatment planning, including anatomical segmentation, beam placement, optimization, dose calculation, and plan documentation. The user specifies clinical requirements of the plan to be generated through a user interface embedded in the planning system. The automated method uses heuristic algorithms to definemore » and simplify the technical aspects of the treatment planning process. Results: Automated planning was used in 1661 of 1708 patients receiving tangential breast IMRT during the time interval studied. Therefore, automated planning was applicable in greater than 97% of cases. The time for treatment planning using the automated process is routinely 5 to 6 minutes on standard commercially available planning hardware. We have shown a consistent reduction in plan rejections from plan reviews through the standard quality control process or weekly quality review multidisciplinary breast rounds as we have automated the planning process for tangential breast IMRT. Clinical plan acceptance increased from 97.3% using our previous semiautomated inverse method to 98.9% using the fully automated method. Conclusions: Automation has become the routine standard method for treatment planning of tangential breast IMRT at our institution and is clinically feasible on a large scale. The method has wide clinical applicability and can add tremendous efficiency, standardization, and quality to the current treatment planning process. The use of automated methods can allow centers to more rapidly adopt IMRT and enhance access to the documented

Automation and intensity modulated radiation therapy for individualized high-quality tangent breast treatment plans.

PubMed

Purdie, Thomas G; Dinniwell, Robert E; Fyles, Anthony; Sharpe, Michael B

2014-11-01

To demonstrate the large-scale clinical implementation and performance of an automated treatment planning methodology for tangential breast intensity modulated radiation therapy (IMRT). Automated planning was used to prospectively plan tangential breast IMRT treatment for 1661 patients between June 2009 and November 2012. The automated planning method emulates the manual steps performed by the user during treatment planning, including anatomical segmentation, beam placement, optimization, dose calculation, and plan documentation. The user specifies clinical requirements of the plan to be generated through a user interface embedded in the planning system. The automated method uses heuristic algorithms to define and simplify the technical aspects of the treatment planning process. Automated planning was used in 1661 of 1708 patients receiving tangential breast IMRT during the time interval studied. Therefore, automated planning was applicable in greater than 97% of cases. The time for treatment planning using the automated process is routinely 5 to 6 minutes on standard commercially available planning hardware. We have shown a consistent reduction in plan rejections from plan reviews through the standard quality control process or weekly quality review multidisciplinary breast rounds as we have automated the planning process for tangential breast IMRT. Clinical plan acceptance increased from 97.3% using our previous semiautomated inverse method to 98.9% using the fully automated method. Automation has become the routine standard method for treatment planning of tangential breast IMRT at our institution and is clinically feasible on a large scale. The method has wide clinical applicability and can add tremendous efficiency, standardization, and quality to the current treatment planning process. The use of automated methods can allow centers to more rapidly adopt IMRT and enhance access to the documented improvements in care for breast cancer patients, using

Integrated assignment and path planning

NASA Astrophysics Data System (ADS)

Murphey, Robert A.

2005-11-01

A surge of interest in unmanned systems has exposed many new and challenging research problems across many fields of engineering and mathematics. These systems have the potential of transforming our society by replacing dangerous and dirty jobs with networks of moving machines. This vision is fundamentally separate from the modern view of robotics in that sophisticated behavior is realizable not by increasing individual vehicle complexity, but instead through collaborative teaming that relies on collective perception, abstraction, decision making, and manipulation. Obvious examples where collective robotics will make an impact include planetary exploration, space structure assembly, remote and undersea mining, hazardous material handling and clean-up, and search and rescue. Nonetheless, the phenomenon driving this technology trend is the increasing reliance of the US military on unmanned vehicles, specifically, aircraft. Only a few years ago, following years of resistance to the use of unmanned systems, the military and civilian leadership in the United States reversed itself and have recently demonstrated surprisingly broad acceptance of increasingly pervasive use of unmanned platforms in defense surveillance, and even attack. However, as rapidly as unmanned systems have gained acceptance, the defense research community has discovered the technical pitfalls that lie ahead, especially for operating collective groups of unmanned platforms. A great deal of talent and energy has been devoted to solving these technical problems, which tend to fall into two categories: resource allocation of vehicles to objectives, and path planning of vehicle trajectories. An extensive amount of research has been conducted in each direction, yet, surprisingly, very little work has considered the integrated problem of assignment and path planning. This dissertation presents a framework for studying integrated assignment and path planning and then moves on to suggest an exact

Assessing the Performance of Human-Automation Collaborative Planning Systems

DTIC Science & Technology

2011-06-01

process- ing and incorporating vast amounts of incoming information into their solutions. How- ever, these algorithms are brittle and unable to account for...planning system, a descriptive Mission Performance measure may address the total travel time on the path or the cost of the path (e.g. total work...minimizing costs or collisions [4, 32, 33]. Error measures for such a path planning system may track how many collisions occur or how much threat

Path planning for planetary rover using extended elevation map

NASA Technical Reports Server (NTRS)

Nakatani, Ichiro; Kubota, Takashi; Yoshimitsu, Tetsuo

1994-01-01

This paper describes a path planning method for planetary rovers to search for paths on planetary surfaces. The planetary rover is required to travel safely over a long distance for many days over unfamiliar terrain. Hence it is very important how planetary rovers process sensory information in order to understand the planetary environment and to make decisions based on that information. As a new data structure for informational mapping, an extended elevation map (EEM) has been introduced, which includes the effect of the size of the rover. The proposed path planning can be conducted in such a way as if the rover were a point while the size of the rover is automatically taken into account. The validity of the proposed methods is verified by computer simulations.

Robotic path-finding in inverse treatment planning for stereotactic radiosurgery with continuous dose delivery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vandewouw, Marlee M., E-mail: marleev@mie.utoronto

Purpose: Continuous dose delivery in radiation therapy treatments has been shown to decrease total treatment time while improving the dose conformity and distribution homogeneity over the conventional step-and-shoot approach. The authors develop an inverse treatment planning method for Gamma Knife® Perfexion™ that continuously delivers dose along a path in the target. Methods: The authors’ method is comprised of two steps: find a path within the target, then solve a mixed integer optimization model to find the optimal collimator configurations and durations along the selected path. Robotic path-finding techniques, specifically, simultaneous localization and mapping (SLAM) using an extended Kalman filter, aremore » used to obtain a path that travels sufficiently close to selected isocentre locations. SLAM is novelly extended to explore a 3D, discrete environment, which is the target discretized into voxels. Further novel extensions are incorporated into the steering mechanism to account for target geometry. Results: The SLAM method was tested on seven clinical cases and compared to clinical, Hamiltonian path continuous delivery, and inverse step-and-shoot treatment plans. The SLAM approach improved dose metrics compared to the clinical plans and Hamiltonian path continuous delivery plans. Beam-on times improved over clinical plans, and had mixed performance compared to Hamiltonian path continuous plans. The SLAM method is also shown to be robust to path selection inaccuracies, isocentre selection, and dose distribution. Conclusions: The SLAM method for continuous delivery provides decreased total treatment time and increased treatment quality compared to both clinical and inverse step-and-shoot plans, and outperforms existing path methods in treatment quality. It also accounts for uncertainty in treatment planning by accommodating inaccuracies.« less

Planning Flight Paths of Autonomous Aerobots

NASA Technical Reports Server (NTRS)

Kulczycki, Eric; Elfes, Alberto; Sharma, Shivanjli

2009-01-01

Algorithms for planning flight paths of autonomous aerobots (robotic blimps) to be deployed in scientific exploration of remote planets are undergoing development. These algorithms are also adaptable to terrestrial applications involving robotic submarines as well as aerobots and other autonomous aircraft used to acquire scientific data or to perform surveying or monitoring functions.

Down the Road...Long Range Planning for Automation.

ERIC Educational Resources Information Center

Texas State Library, Austin. Dept. of Library Development.

The materials in this manual/workbook were prepared to assist participants in a workshop on long-range planning for library automation. Chapters cover the following topics: (1) "What Is Long-Range Planning?" (2) "Why Plan?" (3) "Who Needs to Participate?" (4) "Planning to Plan"; (5) "Determining Needs"; (6) "Description and Introduction"; (7)…

Automated maneuver planning using a fuzzy logic algorithm

NASA Technical Reports Server (NTRS)

Conway, D.; Sperling, R.; Folta, D.; Richon, K.; Defazio, R.

1994-01-01

Spacecraft orbital control requires intensive interaction between the analyst and the system used to model the spacecraft trajectory. For orbits with right mission constraints and a large number of maneuvers, this interaction is difficult or expensive to accomplish in a timely manner. Some automation of maneuver planning can reduce these difficulties for maneuver-intensive missions. One approach to this automation is to use fuzzy logic in the control mechanism. Such a prototype system currently under development is discussed. The Tropical Rainfall Measurement Mission (TRMM) is one of several missions that could benefit from automated maneuver planning. TRMM is scheduled for launch in August 1997. The spacecraft is to be maintained in a 350-km circular orbit throughout the 3-year lifetime of the mission, with very small variations in this orbit allowed. Since solar maximum will occur as early as 1999, the solar activity during the TRMM mission will be increasing. The increasing solar activity will result in orbital maneuvers being performed as often as every other day. The results of automated maneuver planning for the TRMM mission will be presented to demonstrate the prototype of the fuzzy logic tool.

Aircraft path planning for optimal imaging using dynamic cost functions

NASA Astrophysics Data System (ADS)

Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin

2015-05-01

Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.

Planning Paths Through Singularities in the Center of Mass Space

NASA Technical Reports Server (NTRS)

Doggett, William R.; Messner, William C.; Juang, Jer-Nan

1998-01-01

The center of mass space is a convenient space for planning motions that minimize reaction forces at the robot's base or optimize the stability of a mechanism. A unique problem associated with path planning in the center of mass space is the potential existence of multiple center of mass images for a single Cartesian obstacle, since a single center of mass location can correspond to multiple robot joint configurations. The existence of multiple images results in a need to either maintain multiple center of mass obstacle maps or to update obstacle locations when the robot passes through a singularity, such as when it moves from an elbow-up to an elbow-down configuration. To illustrate the concepts presented in this paper, a path is planned for an example task requiring motion through multiple center of mass space maps. The object of the path planning algorithm is to locate the bang- bang acceleration profile that minimizes the robot's base reactions in the presence of a single Cartesian obstacle. To simplify the presentation, only non-redundant robots are considered and joint non-linearities are neglected.

Cooperative path planning for multi-USV based on improved artificial bee colony algorithm

NASA Astrophysics Data System (ADS)

Cao, Lu; Chen, Qiwei

2018-03-01

Due to the complex constraints, more uncertain factors and critical real-time demand of path planning for multiple unmanned surface vehicle (multi-USV), an improved artificial bee colony (I-ABC) algorithm were proposed to solve the model of cooperative path planning for multi-USV. First the Voronoi diagram of battle field space is conceived to generate the optimal area of USVs paths. Then the chaotic searching algorithm is used to initialize the collection of paths, which is regard as foods of the ABC algorithm. With the limited data, the initial collection can search the optimal area of paths perfectly. Finally simulations of the multi-USV path planning under various threats have been carried out. Simulation results verify that the I-ABC algorithm can improve the diversity of nectar source and the convergence rate of algorithm. It can increase the adaptability of dynamic battlefield and unexpected threats for USV.

Two arm robot path planning in a static environment using polytopes and string stretching. Thesis

NASA Technical Reports Server (NTRS)

Schima, Francis J., III

1990-01-01

The two arm robot path planning problem has been analyzed and reduced into components to be simplified. This thesis examines one component in which two Puma-560 robot arms are simultaneously holding a single object. The problem is to find a path between two points around obstacles which is relatively fast and minimizes the distance. The thesis involves creating a structure on which to form an advanced path planning algorithm which could ideally find the optimum path. An actual path planning method is implemented which is simple though effective in most common situations. Given the limits of computer technology, a 'good' path is currently found. Objects in the workspace are modeled with polytopes. These are used because they can be used for rapid collision detection and still provide a representation which is adequate for path planning.

Three-dimensional path planning software-assisted transjugular intrahepatic portosystemic shunt: a technical modification.

PubMed

Tsauo, Jiaywei; Luo, Xuefeng; Ye, Linchao; Li, Xiao

2015-06-01

This study was designed to report our results with a modified technique of three-dimensional (3D) path planning software assisted transjugular intrahepatic portosystemic shunt (TIPS). 3D path planning software was recently developed to facilitate TIPS creation by using two carbon dioxide portograms acquired at least 20° apart to generate a 3D path for overlay needle guidance. However, one shortcoming is that puncturing along the overlay would be technically impossible if the angle of the liver access set and the angle of the 3D path are not the same. To solve this problem, a prototype 3D path planning software was fitted with a utility to calculate the angle of the 3D path. Using this, we modified the angle of the liver access set accordingly during the procedure in ten patients. Failure for technical reasons occurred in three patients (unsuccessful wedged hepatic venography in two cases, software technical failure in one case). The procedure was successful in the remaining seven patients, and only one needle pass was required to obtain portal vein access in each case. The course of puncture was comparable to the 3D path in all patients. No procedure-related complication occurred following the procedures. Adjusting the angle of the liver access set to match the angle of the 3D path determined by the software appears to be a favorable modification to the technique of 3D path planning software assisted TIPS.

Dynamic path planning for mobile robot based on particle swarm optimization

NASA Astrophysics Data System (ADS)

Wang, Yong; Cai, Feng; Wang, Ying

2017-08-01

In the contemporary, robots are used in many fields, such as cleaning, medical treatment, space exploration, disaster relief and so on. The dynamic path planning of robot without collision is becoming more and more the focus of people's attention. A new method of path planning is proposed in this paper. Firstly, the motion space model of the robot is established by using the MAKLINK graph method. Then the A* algorithm is used to get the shortest path from the start point to the end point. Secondly, this paper proposes an effective method to detect and avoid obstacles. When an obstacle is detected on the shortest path, the robot will choose the nearest safety point to move. Moreover, calculate the next point which is nearest to the target. Finally, the particle swarm optimization algorithm is used to optimize the path. The experimental results can prove that the proposed method is more effective.

A Hybrid Metaheuristic DE/CS Algorithm for UCAV Three-Dimension Path Planning

PubMed Central

Wang, Gaige; Guo, Lihong; Duan, Hong; Wang, Heqi; Liu, Luo; Shao, Mingzhen

2012-01-01

Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model. PMID:23193383

A hybrid metaheuristic DE/CS algorithm for UCAV three-dimension path planning.

PubMed

Wang, Gaige; Guo, Lihong; Duan, Hong; Wang, Heqi; Liu, Luo; Shao, Mingzhen

2012-01-01

Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model.

Three-Dimensional Path Planning Software-Assisted Transjugular Intrahepatic Portosystemic Shunt: A Technical Modification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsauo, Jiaywei, E-mail: 80732059@qq.com; Luo, Xuefeng, E-mail: luobo-913@126.com; Ye, Linchao, E-mail: linchao.ye@siemens.com

2015-06-15

PurposeThis study was designed to report our results with a modified technique of three-dimensional (3D) path planning software assisted transjugular intrahepatic portosystemic shunt (TIPS).Methods3D path planning software was recently developed to facilitate TIPS creation by using two carbon dioxide portograms acquired at least 20° apart to generate a 3D path for overlay needle guidance. However, one shortcoming is that puncturing along the overlay would be technically impossible if the angle of the liver access set and the angle of the 3D path are not the same. To solve this problem, a prototype 3D path planning software was fitted with a utility to calculate themore » angle of the 3D path. Using this, we modified the angle of the liver access set accordingly during the procedure in ten patients.ResultsFailure for technical reasons occurred in three patients (unsuccessful wedged hepatic venography in two cases, software technical failure in one case). The procedure was successful in the remaining seven patients, and only one needle pass was required to obtain portal vein access in each case. The course of puncture was comparable to the 3D path in all patients. No procedure-related complication occurred following the procedures.ConclusionsAdjusting the angle of the liver access set to match the angle of the 3D path determined by the software appears to be a favorable modification to the technique of 3D path planning software assisted TIPS.« less

Evolutionistic or revolutionary paths? A PACS maturity model for strategic situational planning.

PubMed

van de Wetering, Rogier; Batenburg, Ronald; Lederman, Reeva

2010-07-01

While many hospitals are re-evaluating their current Picture Archiving and Communication System (PACS), few have a mature strategy for PACS deployment. Furthermore, strategies for implementation, strategic and situational planning methods for the evolution of PACS maturity are scarce in the scientific literature. Consequently, in this paper we propose a strategic planning method for PACS deployment. This method builds upon a PACS maturity model (PMM), based on the elaboration of the strategic alignment concept and the maturity growth path concept previously developed in the PACS domain. First, we review the literature on strategic planning for information systems and information technology and PACS maturity. Secondly, the PMM is extended by applying four different strategic perspectives of the Strategic Alignment Framework whereupon two types of growth paths (evolutionistic and revolutionary) are applied that focus on a roadmap for PMM. This roadmap builds a path to get from one level of maturity and evolve to the next. An extended method for PACS strategic planning is developed. This method defines eight distinctive strategies for PACS strategic situational planning that allow decision-makers in hospitals to decide which approach best suits their hospitals' current situation and future ambition and what in principle is needed to evolve through the different maturity levels. The proposed method allows hospitals to strategically plan for PACS maturation. It is situational in that the required investments and activities depend on the alignment between the hospital strategy and the selected growth path. The inclusion of both strategic alignment and maturity growth path concepts make the planning method rigorous, and provide a framework for further empirical research and clinical practice.

Simulation based optimization on automated fibre placement process

NASA Astrophysics Data System (ADS)

Lei, Shi

2018-02-01

In this paper, a software simulation (Autodesk TruPlan & TruFiber) based method is proposed to optimize the automate fibre placement (AFP) process. Different types of manufacturability analysis are introduced to predict potential defects. Advanced fibre path generation algorithms are compared with respect to geometrically different parts. Major manufacturing data have been taken into consideration prior to the tool paths generation to achieve high success rate of manufacturing.

Optimal Path Planning Program for Autonomous Speed Sprayer in Orchard Using Order-Picking Algorithm

NASA Astrophysics Data System (ADS)

Park, T. S.; Park, S. J.; Hwang, K. Y.; Cho, S. I.

This study was conducted to develop a software program which computes optimal path for autonomous navigation in orchard, especially for speed sprayer. Possibilities of autonomous navigation in orchard were shown by other researches which have minimized distance error between planned path and performed path. But, research of planning an optimal path for speed sprayer in orchard is hardly founded. In this study, a digital map and a database for orchard which contains GPS coordinate information (coordinates of trees and boundary of orchard) and entity information (heights and widths of trees, radius of main stem of trees, disease of trees) was designed. An orderpicking algorithm which has been used for management of warehouse was used to calculate optimum path based on the digital map. Database for digital map was created by using Microsoft Access and graphic interface for database was made by using Microsoft Visual C++ 6.0. It was possible to search and display information about boundary of an orchard, locations of trees, daily plan for scattering chemicals and plan optimal path on different orchard based on digital map, on each circumstance (starting speed sprayer in different location, scattering chemicals for only selected trees).

Research and application of genetic algorithm in path planning of logistics distribution vehicle

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

The core of the logistics distribution system is the vehicle routing planning, research path planning problem, provide a better solution has become an important issue. In order to provide the decision support for logistics and distribution operations, this paper studies the problem of vehicle routing with capacity constraints (CVRP). By establishing a mathematical model, the genetic algorithm is used to plan the path of the logistics vehicle to meet the minimum logistics and transportation costs.

A Comparison of Risk Sensitive Path Planning Methods for Aircraft Emergency Landing

NASA Technical Reports Server (NTRS)

Meuleau, Nicolas; Plaunt, Christian; Smith, David E.; Smith, Tristan

2009-01-01

Determining the best site to land a damaged aircraft presents some interesting challenges for standard path planning techniques. There are multiple possible locations to consider, the space is 3-dimensional with dynamics, the criteria for a good path is determined by overall risk rather than distance or time, and optimization really matters, since an improved path corresponds to greater expected survival rate. We have investigated a number of different path planning methods for solving this problem, including cell decomposition, visibility graphs, probabilistic road maps (PRMs), and local search techniques. In their pure form, none of these techniques have proven to be entirely satisfactory - some are too slow or unpredictable, some produce highly non-optimal paths or do not find certain types of paths, and some do not cope well with the dynamic constraints when controllability is limited. In the end, we are converging towards a hybrid technique that involves seeding a roadmap with a layered visibility graph, using PRM to extend that roadmap, and using local search to further optimize the resulting paths. We describe the techniques we have investigated, report on our experiments with these techniques, and discuss when and why various techniques were unsatisfactory.

Safe Maritime Autonomous Path Planning in a High Sea State

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Quadrelli, Marco; Huntsberger, Terrance L.

2014-01-01

This paper presents a path planning method for sea surface vehicles that prevents capsizing and bow-diving in a high sea-state. A key idea is to use response amplitude operators (RAOs) or, in control terminology, the transfer functions from a sea state to a vessel's motion, in order to find a set of speeds and headings that results in excessive pitch and roll oscillations. This information is translated to arithmetic constraints on the ship's velocity, which are passed to a model predictive control (MPC)-based path planner to find a safe and optimal path that achieves specified goals. An obstacle avoidance capability is also added to the path planner. The proposed method is demonstrated by simulations.

Robotic Online Path Planning on Point Cloud.

PubMed

Liu, Ming

2016-05-01

This paper deals with the path-planning problem for mobile wheeled- or tracked-robot which drive in 2.5-D environments, where the traversable surface is usually considered as a 2-D-manifold embedded in a 3-D ambient space. Specially, we aim at solving the 2.5-D navigation problem using raw point cloud as input. The proposed method is independent of traditional surface parametrization or reconstruction methods, such as a meshing process, which generally has high-computational complexity. Instead, we utilize the output of 3-D tensor voting framework on the raw point clouds. The computation of tensor voting is accelerated by optimized implementation on graphics computation unit. Based on the tensor voting results, a novel local Riemannian metric is defined using the saliency components, which helps the modeling of the latent traversable surface. Using the proposed metric, we prove that the geodesic in the 3-D tensor space leads to rational path-planning results by experiments. Compared to traditional methods, the results reveal the advantages of the proposed method in terms of smoothing the robot maneuver while considering the minimum travel distance.

The force control and path planning of electromagnetic induction-based massage robot.

PubMed

Wang, Wendong; Zhang, Lei; Li, Jinzhe; Yuan, Xiaoqing; Shi, Yikai; Jiang, Qinqin; He, Lijing

2017-07-20

Massage robot is considered as an effective physiological treatment to relieve fatigue, improve blood circulation, relax muscle tone, etc. The simple massage equipment quickly spread into market due to low cost, but they are not widely accepted due to restricted massage function. Complicated structure and high cost caused difficulties for developing multi-function massage equipment. This paper presents a novel massage robot which can achieve tapping, rolling, kneading and other massage operations, and proposes an improved reciprocating path planning algorithm to improve massage effect. The number of coil turns, the coil current and the distance between massage head and yoke were chosen to investigate the influence on massage force by finite element method. The control system model of the wheeled massage robot was established, including control subsystem of the motor, path algorithm control subsystem, parameter module of the massage robot and virtual reality interface module. The improved reciprocating path planning algorithm was proposed to improve regional coverage rate and massage effect. The influence caused by coil current, the number of coil turns and the distance between massage head and yoke were simulated in Maxwell. It indicated that coil current has more important influence compared to the other two factors. The path planning simulation of the massage robot was completed in Matlab, and the results show that the improved reciprocating path planning algorithm achieved higher coverage rate than the traditional algorithm. With the analysis of simulation results, it can be concluded that the number of coil turns and the distance between the moving iron core and the yoke could be determined prior to coil current, and the force can be controllable by optimizing structure parameters of massage head and adjusting coil current. Meanwhile, it demonstrates that the proposed algorithm could effectively improve path coverage rate during massage operations, therefore

Automated planning of MRI scans of knee joints

NASA Astrophysics Data System (ADS)

Bystrov, Daniel; Pekar, Vladimir; Young, Stewart; Dries, Sebastian P. M.; Heese, Harald S.; van Muiswinkel, Arianne M.

2007-03-01

A novel and robust method for automatic scan planning of MRI examinations of knee joints is presented. Clinical knee examinations require acquisition of a 'scout' image, in which the operator manually specifies the scan volume orientations (off-centres, angulations, field-of-view) for the subsequent diagnostic scans. This planning task is time-consuming and requires skilled operators. The proposed automated planning system determines orientations for the diagnostic scan by using a set of anatomical landmarks derived by adapting active shape models of the femur, patella and tibia to the acquired scout images. The expert knowledge required to position scan geometries is learned from previous manually planned scans, allowing individual preferences to be taken into account. The system is able to automatically discriminate between left and right knees. This allows to use and merge training data from both left and right knees, and to automatically transform all learned scan geometries to the side for which a plan is required, providing a convenient integration of the automated scan planning system in the clinical routine. Assessment of the method on the basis of 88 images from 31 different individuals, exhibiting strong anatomical and positional variability demonstrates success, robustness and efficiency of all parts of the proposed approach, which thus has the potential to significantly improve the clinical workflow.

Iterative dataset optimization in automated planning: Implementation for breast and rectal cancer radiotherapy.

PubMed

Fan, Jiawei; Wang, Jiazhou; Zhang, Zhen; Hu, Weigang

2017-06-01

To develop a new automated treatment planning solution for breast and rectal cancer radiotherapy. The automated treatment planning solution developed in this study includes selection of the iterative optimized training dataset, dose volume histogram (DVH) prediction for the organs at risk (OARs), and automatic generation of clinically acceptable treatment plans. The iterative optimized training dataset is selected by an iterative optimization from 40 treatment plans for left-breast and rectal cancer patients who received radiation therapy. A two-dimensional kernel density estimation algorithm (noted as two parameters KDE) which incorporated two predictive features was implemented to produce the predicted DVHs. Finally, 10 additional new left-breast treatment plans are re-planned using the Pinnacle 3 Auto-Planning (AP) module (version 9.10, Philips Medical Systems) with the objective functions derived from the predicted DVH curves. Automatically generated re-optimized treatment plans are compared with the original manually optimized plans. By combining the iterative optimized training dataset methodology and two parameters KDE prediction algorithm, our proposed automated planning strategy improves the accuracy of the DVH prediction. The automatically generated treatment plans using the dose derived from the predicted DVHs can achieve better dose sparing for some OARs without compromising other metrics of plan quality. The proposed new automated treatment planning solution can be used to efficiently evaluate and improve the quality and consistency of the treatment plans for intensity-modulated breast and rectal cancer radiation therapy. © 2017 American Association of Physicists in Medicine.

Sampling-Based Coverage Path Planning for Complex 3D Structures

DTIC Science & Technology

2012-09-01

one such task, in which a single robot must sweep its end effector over the entirety of a known workspace. For two-dimensional environments, optimal...structures. First, we introduce a new algorithm for planning feasible coverage paths. It is more computationally efficient in problems of complex geometry...iteratively shortens and smooths a feasible coverage path; robot configurations are adjusted without violating any coverage con- straints. Third, we propose

Planning nonlinear access paths for temporal bone surgery.

PubMed

Fauser, Johannes; Sakas, Georgios; Mukhopadhyay, Anirban

2018-05-01

Interventions at the otobasis operate in the narrow region of the temporal bone where several highly sensitive organs define obstacles with minimal clearance for surgical instruments. Nonlinear trajectories for potential minimally invasive interventions can provide larger distances to risk structures and optimized orientations of surgical instruments, thus improving clinical outcomes when compared to existing linear approaches. In this paper, we present fast and accurate planning methods for such nonlinear access paths. We define a specific motion planning problem in [Formula: see text] with notable constraints in computation time and goal pose that reflect the requirements of temporal bone surgery. We then present [Formula: see text]-RRT-Connect: two suitable motion planners based on bidirectional Rapidly exploring Random Tree (RRT) to solve this problem efficiently. The benefits of [Formula: see text]-RRT-Connect are demonstrated on real CT data of patients. Their general performance is shown on a large set of realistic synthetic anatomies. We also show that these new algorithms outperform state-of-the-art methods based on circular arcs or Bézier-Splines when applied to this specific problem. With this work, we demonstrate that preoperative and intra-operative planning of nonlinear access paths is possible for minimally invasive surgeries at the otobasis.

Knowledge Acquisition, Validation, and Maintenance in a Planning System for Automated Image Processing

NASA Technical Reports Server (NTRS)

Chien, Steve A.

1996-01-01

A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintainting the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems. This paper describes a planning application of automated imaging processing and our overall approach to knowledge acquisition for this application.

Pedestrian flow-path modeling to support tsunami-evacuation planning

NASA Astrophysics Data System (ADS)

Wood, N. J.; Jones, J. M.; Schmidtlein, M.

2015-12-01

Near-field tsunami hazards are credible threats to many coastal communities throughout the world. Along the U.S. Pacific Northwest coast, low-lying areas could be inundated by a series of catastrophic tsunamis potentially arriving in a matter of minutes following a Cascadia subduction zone (CSZ) earthquake. We developed a geospatial-modeling method for characterizing pedestrian-evacuation flow paths and evacuation basins to support evacuation and relief planning efforts for coastal communities in this region. We demonstrate this approach using the coastal communities of Aberdeen, Hoquiam, and Cosmopolis in southwestern Grays Harbor County, Washington (USA), where previous research suggests approximately 20,500 people (99% of the residents in tsunami-hazard zones) will likely have enough time to evacuate before tsunami-wave arrival. Geospatial, anisotropic, path distance models were developed to map the most efficient pedestrian paths to higher ground from locations within the tsunami-hazard zone. This information was then used to identify evacuation basins, outlining neighborhoods sharing a common evacuation pathway to safety. We then estimated the number of people traveling along designated evacuation pathways and arriving at pre-determined safe assembly areas, helping determine shelter demand and relief support (e.g., for elderly individuals or tourists). Finally, we assessed which paths may become inaccessible due to earthquake-induced ground failures, a factor which may impact an individual's success in reaching safe ground. The presentation will include a discussion of the implications of our analysis for developing more comprehensive coastal community tsunami-evacuation planning strategies worldwide.

Real-time path planning and autonomous control for helicopter autorotation

NASA Astrophysics Data System (ADS)

Yomchinda, Thanan

Autorotation is a descending maneuver that can be used to recover helicopters in the event of total loss of engine power; however it is an extremely difficult and complex maneuver. The objective of this work is to develop a real-time system which provides full autonomous control for autorotation landing of helicopters. The work includes the development of an autorotation path planning method and integration of the path planner with a primary flight control system. The trajectory is divided into three parts: entry, descent and flare. Three different optimization algorithms are used to generate trajectories for each of these segments. The primary flight control is designed using a linear dynamic inversion control scheme, and a path following control law is developed to track the autorotation trajectories. Details of the path planning algorithm, trajectory following control law, and autonomous autorotation system implementation are presented. The integrated system is demonstrated in real-time high fidelity simulations. Results indicate feasibility of the capability of the algorithms to operate in real-time and of the integrated systems ability to provide safe autorotation landings. Preliminary simulations of autonomous autorotation on a small UAV are presented which will lead to a final hardware demonstration of the algorithms.

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR

PubMed Central

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-01-01

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner. PMID:29439447

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.

PubMed

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-02-11

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.

Visual environment recognition for robot path planning using template matched filters

NASA Astrophysics Data System (ADS)

Orozco-Rosas, Ulises; Picos, Kenia; Díaz-Ramírez, Víctor H.; Montiel, Oscar; Sepúlveda, Roberto

2017-08-01

A visual approach in environment recognition for robot navigation is proposed. This work includes a template matching filtering technique to detect obstacles and feasible paths using a single camera to sense a cluttered environment. In this problem statement, a robot can move from the start to the goal by choosing a single path between multiple possible ways. In order to generate an efficient and safe path for mobile robot navigation, the proposal employs a pseudo-bacterial potential field algorithm to derive optimal potential field functions using evolutionary computation. Simulation results are evaluated in synthetic and real scenes in terms of accuracy of environment recognition and efficiency of path planning computation.

Planning representation for automated exploratory data analysis

NASA Astrophysics Data System (ADS)

St. Amant, Robert; Cohen, Paul R.

1994-03-01

Igor is a knowledge-based system for exploratory statistical analysis of complex systems and environments. Igor has two related goals: to help automate the search for interesting patterns in data sets, and to help develop models that capture significant relationships in the data. We outline a language for Igor, based on techniques of opportunistic planning, which balances control and opportunism. We describe the application of Igor to the analysis of the behavior of Phoenix, an artificial intelligence planning system.

Application of ant colony algorithm in path planning of the data center room robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Ma, Jianming; Wang, Ying

2017-05-01

According to the Internet Data Center (IDC) room patrol robot as the background, the robot in the search path of autonomous obstacle avoidance and path planning ability, worked out in advance of the robot room patrol mission. The simulation experimental results show that the improved ant colony algorithm for IDC room patrol robot obstacle avoidance planning, makes the robot along an optimal or suboptimal and safe obstacle avoidance path to reach the target point to complete the task. To prove the feasibility of the method.

Reasoning on the Self-Organizing Incremental Associative Memory for Online Robot Path Planning

NASA Astrophysics Data System (ADS)

Kawewong, Aram; Honda, Yutaro; Tsuboyama, Manabu; Hasegawa, Osamu

Robot path-planning is one of the important issues in robotic navigation. This paper presents a novel robot path-planning approach based on the associative memory using Self-Organizing Incremental Neural Networks (SOINN). By the proposed method, an environment is first autonomously divided into a set of path-fragments by junctions. Each fragment is represented by a sequence of preliminarily generated common patterns (CPs). In an online manner, a robot regards the current path as the associative path-fragments, each connected by junctions. The reasoning technique is additionally proposed for decision making at each junction to speed up the exploration time. Distinct from other methods, our method does not ignore the important information about the regions between junctions (path-fragments). The resultant number of path-fragments is also less than other method. Evaluation is done via Webots physical 3D-simulated and real robot experiments, where only distance sensors are available. Results show that our method can represent the environment effectively; it enables the robot to solve the goal-oriented navigation problem in only one episode, which is actually less than that necessary for most of the Reinforcement Learning (RL) based methods. The running time is proved finite and scales well with the environment. The resultant number of path-fragments matches well to the environment.

Current-Sensitive Path Planning for an Underactuated Free-Floating Ocean Sensorweb

NASA Technical Reports Server (NTRS)

Dahl, Kristen P.; Thompson, David R.; McLaren, David; Chao, Yi; Chien, Steve

2011-01-01

This work investigates multi-agent path planning in strong, dynamic currents using thousands of highly under-actuated vehicles. We address the specific task of path planning for a global network of ocean-observing floats. These submersibles are typified by the Argo global network consisting of over 3000 sensor platforms. They can control their buoyancy to float at depth for data collection or rise to the surface for satellite communications. Currently, floats drift at a constant depth regardless of the local currents. However, accurate current forecasts have become available which present the possibility of intentionally controlling floats' motion by dynamically commanding them to linger at different depths. This project explores the use of these current predictions to direct float networks to some desired final formation or position. It presents multiple algorithms for such path optimization and demonstrates their advantage over the standard approach of constant-depth drifting.

Path planning of decentralized multi-quadrotor based on fuzzy-cell decomposition algorithm

NASA Astrophysics Data System (ADS)

Iswanto, Wahyunggoro, Oyas; Cahyadi, Adha Imam

2017-04-01

The paper aims to present a design algorithm for multi quadrotor lanes in order to move towards the goal quickly and avoid obstacles in an area with obstacles. There are several problems in path planning including how to get to the goal position quickly and avoid static and dynamic obstacles. To overcome the problem, therefore, the paper presents fuzzy logic algorithm and fuzzy cell decomposition algorithm. Fuzzy logic algorithm is one of the artificial intelligence algorithms which can be applied to robot path planning that is able to detect static and dynamic obstacles. Cell decomposition algorithm is an algorithm of graph theory used to make a robot path map. By using the two algorithms the robot is able to get to the goal position and avoid obstacles but it takes a considerable time because they are able to find the shortest path. Therefore, this paper describes a modification of the algorithms by adding a potential field algorithm used to provide weight values on the map applied for each quadrotor by using decentralized controlled, so that the quadrotor is able to move to the goal position quickly by finding the shortest path. The simulations conducted have shown that multi-quadrotor can avoid various obstacles and find the shortest path by using the proposed algorithms.

ISS Operations Cost Reductions Through Automation of Real-Time Planning Tasks

NASA Technical Reports Server (NTRS)

Hall, Timothy A.

2011-01-01

In 2008 the Johnson Space Center s Mission Operations Directorate (MOD) management team challenged their organization to find ways to reduce the costs of International Space station (ISS) console operations in the Mission Control Center (MCC). Each MOD organization was asked to identify projects that would help them attain a goal of a 30% reduction in operating costs by 2012. The MOD Operations and Planning organization responded to this challenge by launching several software automation projects that would allow them to greatly improve ISS console operations and reduce staffing and operating costs. These projects to date have allowed the MOD Operations organization to remove one full time (7 x 24 x 365) ISS console position in 2010; with the plan of eliminating two full time ISS console support positions by 2012. This will account for an overall 10 EP reduction in staffing for the Operations and Planning organization. These automation projects focused on utilizing software to automate many administrative and often repetitive tasks involved with processing ISS planning and daily operations information. This information was exchanged between the ground flight control teams in Houston and around the globe, as well as with the ISS astronaut crew. These tasks ranged from managing mission plan changes from around the globe, to uploading and downloading information to and from the ISS crew, to even more complex tasks that required multiple decision points to process the data, track approvals and deliver it to the correct recipient across network and security boundaries. The software solutions leveraged several different technologies including customized web applications and implementation of industry standard web services architecture between several planning tools; as well as a engaging a previously research level technology (TRL 2-3) developed by Ames Research Center (ARC) that utilized an intelligent agent based system to manage and automate file traffic flow

An Obstacle-Tolerant Path Planning Algorithm for Mobile-Anchor-Node-Assisted Localization

PubMed Central

Tsai, Rong-Guei

2018-01-01

The location information obtained using a sensor is a critical requirement in wireless sensor networks. Numerous localization schemes have been proposed, among which mobile-anchor-node-assisted localization (MANAL) can reduce costs and overcome environmental constraints. A mobile anchor node (MAN) provides its own location information to assist the localization of sensor nodes. Numerous path planning schemes have been proposed for MANAL, but most scenarios assume the absence of obstacles in the environment. However, in a realistic environment, sensor nodes cannot be located because the obstacles block the path traversed by the MAN, thereby rendering the sensor incapable of receiving sufficient three location information from the MAN. This study proposes the obstacle-tolerant path planning (OTPP) approach to solve the sensor location problem owing to obstacle blockage. OTPP can approximate the optimum beacon point number and path planning, thereby ensuring that all the unknown nodes can receive the three location information from the MAN and reduce the number of MAN broadcast packet times. Experimental results demonstrate that OTPP performs better than Z-curves because it reduces the total number of beacon points utilized and is thus more suitable in an obstacle-present environment. Compared to the Z-curve, OTPP can reduce localization error and improve localization coverage. PMID:29547582

Finding Out Critical Points For Real-Time Path Planning

NASA Astrophysics Data System (ADS)

Chen, Wei

1989-03-01

Path planning for a mobile robot is a classic topic, but the path planning under real-time environment is a different issue. The system sources including sampling time, processing time, processes communicating time, and memory space are very limited for this type of application. This paper presents a method which abstracts the world representation from the sensory data and makes the decision as to which point will be a potentially critical point to span the world map by using incomplete knowledge about physical world and heuristic rule. Without any previous knowledge or map of the workspace, the robot will determine the world map by roving through the workspace. The computational complexity for building and searching such a map is not more than O( n2 ) The find-path problem is well-known in robotics. Given an object with an initial location and orientation, a goal location and orientation, and a set of obstacles located in space, the problem is to find a continuous path for the object from the initial position to the goal position which avoids collisions with obstacles along the way. There are a lot of methods to find a collision-free path in given environment. Techniques for solving this problem can be classified into three approaches: 1) the configuration space approach [1],[2],[3] which represents the polygonal obstacles by vertices in a graph. The idea is to determine those parts of the free space which a reference point of the moving object can occupy without colliding with any obstacles. A path is then found for the reference point through this truly free space. Dealing with rotations turns out to be a major difficulty with the approach, requiring complex geometric algorithms which are computationally expensive. 2) the direct representation of the free space using basic shape primitives such as convex polygons [4] and overlapping generalized cones [5]. 3) the combination of technique 1 and 2 [6] by which the space is divided into the primary convex region

An Application of Self-Organizing Map for Multirobot Multigoal Path Planning with Minmax Objective.

PubMed

Faigl, Jan

2016-01-01

In this paper, Self-Organizing Map (SOM) for the Multiple Traveling Salesman Problem (MTSP) with minmax objective is applied to the robotic problem of multigoal path planning in the polygonal domain. The main difficulty of such SOM deployment is determination of collision-free paths among obstacles that is required to evaluate the neuron-city distances in the winner selection phase of unsupervised learning. Moreover, a collision-free path is also needed in the adaptation phase, where neurons are adapted towards the presented input signal (city) to the network. Simple approximations of the shortest path are utilized to address this issue and solve the robotic MTSP by SOM. Suitability of the proposed approximations is verified in the context of cooperative inspection, where cities represent sensing locations that guarantee to "see" the whole robots' workspace. The inspection task formulated as the MTSP-Minmax is solved by the proposed SOM approach and compared with the combinatorial heuristic GENIUS. The results indicate that the proposed approach provides competitive results to GENIUS and support applicability of SOM for robotic multigoal path planning with a group of cooperating mobile robots. The proposed combination of approximate shortest paths with unsupervised learning opens further applications of SOM in the field of robotic planning.

An Application of Self-Organizing Map for Multirobot Multigoal Path Planning with Minmax Objective

PubMed Central

Faigl, Jan

2016-01-01

In this paper, Self-Organizing Map (SOM) for the Multiple Traveling Salesman Problem (MTSP) with minmax objective is applied to the robotic problem of multigoal path planning in the polygonal domain. The main difficulty of such SOM deployment is determination of collision-free paths among obstacles that is required to evaluate the neuron-city distances in the winner selection phase of unsupervised learning. Moreover, a collision-free path is also needed in the adaptation phase, where neurons are adapted towards the presented input signal (city) to the network. Simple approximations of the shortest path are utilized to address this issue and solve the robotic MTSP by SOM. Suitability of the proposed approximations is verified in the context of cooperative inspection, where cities represent sensing locations that guarantee to “see” the whole robots' workspace. The inspection task formulated as the MTSP-Minmax is solved by the proposed SOM approach and compared with the combinatorial heuristic GENIUS. The results indicate that the proposed approach provides competitive results to GENIUS and support applicability of SOM for robotic multigoal path planning with a group of cooperating mobile robots. The proposed combination of approximate shortest paths with unsupervised learning opens further applications of SOM in the field of robotic planning. PMID:27340395

Traverse Planning with Temporal-Spatial Constraints

NASA Technical Reports Server (NTRS)

Bresina, John L.; Morris, Paul H.; Deans, Mathew C.; Cohen, Tamar E.; Lees, David S.

2017-01-01

We present an approach to planning rover traverses in a domain that includes temporal-spatial constraints. We are using the NASA Resource Prospector mission as a reference mission in our research. The objective of this mission is to explore permanently shadowed regions at a Lunar pole. Most of the time the rover is required to avoid being in shadow. This requirement depends on where the rover is located and when it is at that location. Such a temporal-spatial constraint makes traverse planning more challenging for both humans and machines. We present a mixed-initiative traverse planner which addresses this challenge. This traverse planner is part of the Exploration Ground Data Systems (xGDS), which we have enhanced with new visualization features, new analysis tools, and new automation for path planning, in order to be applicable to the Re-source Prospector mission. The key concept that is the basis of the analysis tools and that supports the automated path planning is reachability in this dynamic environment due to the temporal-spatial constraints.

Automated survey of 8000 plan checks at eight facilities.

PubMed

Halabi, Tarek; Lu, Hsiao-Ming; Bernard, Damian A; Chu, James C H; Kirk, Michael C; Hamilton, Russell J; Lei, Yu; Driewer, Joseph

2016-09-01

To identify policy and system related weaknesses in treatment planning and plan check work-flows. The authors' web deployed plan check automation solution, PlanCheck, which works with all major planning and record and verify systems (demonstrated here for mosaiq only), allows them to compute violation rates for a large number of plan checks across many facilities without requiring the manual data entry involved with incident filings. Workflows and failure modes are heavily influenced by the type of record and verify system used. Rather than tackle multiple record and verify systems at once, the authors restricted the present survey to mosaiq facilities. Violations were investigated by sending inquiries to physicists running the program. Frequent violations included inadequate tracking in the record and verify system of total and prescription doses. Infrequent violations included incorrect setting of patient orientation in the record and verify system. Peaks in the distribution, over facilities, of violation frequencies pointed to suboptimal policies at some of these facilities. Correspondence with physicists often revealed incomplete knowledge of settings at their facility necessary to perform thorough plan checks. The survey leads to the identification of specific and important policy and system deficiencies that include: suboptimal timing of initial plan checks, lack of communication or agreement on conventions surrounding prescription definitions, and lack of automation in the transfer of some parameters.

Application of particle swarm optimization in path planning of mobile robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Cai, Feng; Wang, Ying

2017-08-01

In order to realize the optimal path planning of mobile robot in unknown environment, a particle swarm optimization algorithm based on path length as fitness function is proposed. The location of the global optimal particle is determined by the minimum fitness value, and the robot moves along the points of the optimal particles to the target position. The process of moving to the target point is done with MATLAB R2014a. Compared with the standard particle swarm optimization algorithm, the simulation results show that this method can effectively avoid all obstacles and get the optimal path.

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System

PubMed Central

Court, Laurence E.; Kisling, Kelly; McCarroll, Rachel; Zhang, Lifei; Yang, Jinzhong; Simonds, Hannah; du Toit, Monique; Trauernicht, Chris; Burger, Hester; Parkes, Jeannette; Mejia, Mike; Bojador, Maureen; Balter, Peter; Branco, Daniela; Steinmann, Angela; Baltz, Garrett; Gay, Skylar; Anderson, Brian; Cardenas, Carlos; Jhingran, Anuja; Shaitelman, Simona; Bogler, Oliver; Schmeller, Kathleen; Followill, David; Howell, Rebecca; Nelson, Christopher; Peterson, Christine; Beadle, Beth

2018-01-01

The Radiation Planning Assistant (RPA) is a system developed for the fully automated creation of radiotherapy treatment plans, including volume-modulated arc therapy (VMAT) plans for patients with head/neck cancer and 4-field box plans for patients with cervical cancer. It is a combination of specially developed in-house software that uses an application programming interface to communicate with a commercial radiotherapy treatment planning system. It also interfaces with a commercial secondary dose verification software. The necessary inputs to the system are a Treatment Plan Order, approved by the radiation oncologist, and a simulation computed tomography (CT) image, approved by the radiographer. The RPA then generates a complete radiotherapy treatment plan. For the cervical cancer treatment plans, no additional user intervention is necessary until the plan is complete. For head/neck treatment plans, after the normal tissue and some of the target structures are automatically delineated on the CT image, the radiation oncologist must review the contours, making edits if necessary. They also delineate the gross tumor volume. The RPA then completes the treatment planning process, creating a VMAT plan. Finally, the completed plan must be reviewed by qualified clinical staff. PMID:29708544

A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm.

PubMed

Wei, Kun; Ren, Bingyin

2018-02-13

In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human-Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among the path-planning methods, the Rapidly Exploring Random Tree (RRT) algorithm based on random sampling has been widely applied in dynamic path planning for a high-dimensional robotic manipulator, especially in a complex environment because of its probability completeness, perfect expansion, and fast exploring speed over other planning methods. However, the existing RRT algorithm has a limitation in path planning for a robotic manipulator in a dynamic unstructured environment. Therefore, an autonomous obstacle avoidance dynamic path-planning method for a robotic manipulator based on an improved RRT algorithm, called Smoothly RRT (S-RRT), is proposed. This method that targets a directional node extends and can increase the sampling speed and efficiency of RRT dramatically. A path optimization strategy based on the maximum curvature constraint is presented to generate a smooth and curved continuous executable path for a robotic manipulator. Finally, the correctness, effectiveness, and practicability of the proposed method are demonstrated and validated via a MATLAB static simulation and a Robot Operating System (ROS) dynamic simulation environment as well as a real autonomous obstacle avoidance experiment in a dynamic unstructured environment for a robotic manipulator. The proposed method not only provides great practical engineering significance for a robotic manipulator's obstacle avoidance in an intelligent factory, but also theoretical reference value for other type of robots' path planning.

Path planning and energy management of solar-powered unmanned ground vehicles

NASA Astrophysics Data System (ADS)

Kaplan, Adam

Many of the applications pertinent to unmanned vehicles, such as environmental research and analysis, communications, and information-surveillance and reconnaissance, benefit from prolonged vehicle operation time. Conventional efforts to increase the operational time of electric-powered unmanned vehicles have traditionally focused on the design of energy-efficient components and the identification of energy efficient search patterns, while little attention has been paid to the vehicle's mission-level path plan and power management. This thesis explores the formulation and generation of integrated motion-plans and power-schedules for solar-panel equipped mobile robots operating under strict energy constraints, which cannot be effectively addressed through conventional motion planning algorithms. Transit problems are considered to design time-optimal paths using both Balkcom-Mason and Pseudo-Dubins curves. Additionally, a more complicated problem to generate mission plans for vehicles which must persistently travel between certain locations, similar to the traveling salesperson problem (TSP), is presented. A comparison between one of the common motion-planning algorithms and experimental results of the prescribed algorithms, made possible by use of a test environment and mobile robot designed and developed specifically for this research, are presented and discussed.

Space station automation: the role of robotics and artificial intelligence (Invited Paper)

NASA Astrophysics Data System (ADS)

Park, W. T.; Firschein, O.

1985-12-01

Automation of the space station is necessary to make more effective use of the crew, to carry out repairs that are impractical or dangerous, and to monitor and control the many space station subsystems. Intelligent robotics and expert systems play a strong role in automation, and both disciplines are highly dependent on a common artificial intelligence (Al) technology base. The AI technology base provides the reasoning and planning capabilities needed in robotic tasks, such as perception of the environment and planning a path to a goal, and in expert systems tasks, such as control of subsystems and maintenance of equipment. This paper describes automation concepts for the space station, the specific robotic and expert systems required to attain this automation, and the research and development required. It also presents an evolutionary development plan that leads to fully automatic mobile robots for servicing satellites. Finally, we indicate the sequence of demonstrations and the research and development needed to confirm the automation capabilities. We emphasize that advanced robotics requires AI, and that to advance, AI needs the "real-world" problems provided by robotics.

The Automated Logistics Element Planning System (ALEPS)

NASA Technical Reports Server (NTRS)

Schwaab, Douglas G.

1992-01-01

ALEPS, which is being developed to provide the SSF program with a computer system to automate logistics resupply/return cargo load planning and verification, is presented. ALEPS will make it possible to simultaneously optimize both the resupply flight load plan and the return flight reload plan for any of the logistics carriers. In the verification mode ALEPS will support the carrier's flight readiness reviews and control proper execution of the approved plans. It will also support the SSF inventory management system by providing electronic block updates to the inventory database on the cargo arriving at or departing the station aboard a logistics carrier. A prototype drawer packing algorithm is described which is capable of generating solutions for 3D packing of cargo items into a logistics carrier storage accommodation. It is concluded that ALEPS will provide the capability to generate and modify optimized loading plans for the logistics elements fleet.

A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles

PubMed Central

2017-01-01

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently. PMID:28255297

A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles.

PubMed

Ni, Jianjun; Wu, Liuying; Shi, Pengfei; Yang, Simon X

2017-01-01

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.

Path planning in uncertain flow fields using ensemble method

NASA Astrophysics Data System (ADS)

Wang, Tong; Le Maître, Olivier P.; Hoteit, Ibrahim; Knio, Omar M.

2016-10-01

An ensemble-based approach is developed to conduct optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where an ensemble of deterministic predictions is used to model and quantify uncertainty. In an operational setting, much about dynamics, topography, and forcing of the ocean environment is uncertain. To address this uncertainty, the flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each of the resulting realizations of the uncertain current field, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of the sampling strategy and to develop insight into extensions dealing with general circulation ocean models. In particular, the ensemble method enables us to perform a statistical analysis of travel times and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.

Robot path planning using expert systems and machine vision

NASA Astrophysics Data System (ADS)

Malone, Denis E.; Friedrich, Werner E.

1992-02-01

This paper describes a system developed for the robotic processing of naturally variable products. In order to plan the robot motion path it was necessary to use a sensor system, in this case a machine vision system, to observe the variations occurring in workpieces and interpret this with a knowledge based expert system. The knowledge base was acquired by carrying out an in-depth study of the product using examination procedures not available in the robotic workplace and relates the nature of the required path to the information obtainable from the machine vision system. The practical application of this system to the processing of fish fillets is described and used to illustrate the techniques.

Automated construction of an intraoperative high-dose-rate treatment plan library for the Varian brachytherapy treatment planning system.

PubMed

Deufel, Christopher L; Furutani, Keith M; Dahl, Robert A; Haddock, Michael G

2016-01-01

The ability to create treatment plans for intraoperative high-dose-rate (IOHDR) brachytherapy is limited by lack of imaging and time constraints. An automated method for creation of a library of high-dose-rate brachytherapy plans that can be used with standard planar applicators in the intraoperative setting is highly desirable. Nonnegative least squares algebraic methods were used to identify dwell time values for flat, rectangular planar applicators. The planar applicators ranged in length and width from 2 cm to 25 cm. Plans were optimized to deliver an absorbed dose of 10 Gy to three different depths from the patient surface: 0 cm, 0.5 cm, and 1.0 cm. Software was written to calculate the optimized dwell times and insert dwell times and positions into a .XML plan template that can be imported into the Varian brachytherapy treatment planning system. The user may import the .XML template into the treatment planning system in the intraoperative setting to match the patient applicator size and prescribed treatment depth. A total of 1587 library plans were created for IOHDR brachytherapy. Median plan generation time was approximately 1 minute per plan. Plan dose was typically 100% ± 1% (mean, standard deviation) of the prescribed dose over the entire length and width of the applicator. Plan uniformity was best for prescription depths of 0 cm and 0.5 cm from the patient surface. An IOHDR plan library may be created using automated methods. Thousands of plan templates may be optimized and prepared in a few hours to accommodate different applicator sizes and treatment depths and reduce treatment planning time. The automated method also enforces dwell time symmetry for symmetrical applicator geometries, which simplifies quality assurance. Copyright © 2016 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Automation--planning to implementation; the problems en route.

PubMed Central

Pizer, I H

1976-01-01

Once the major decision to automate library processes is made, there are a variety of problems which may be encountered before the planned system becomes operational. These include problems of personnel, budget, procurement of adjunct services, institutional priorities, and manufacturing uncertainties. Actual and potential difficulties are discussed. PMID:1247703

SU-E-T-502: Initial Results of a Comparison of Treatment Plans Produced From Automated Prioritized Planning Method and a Commercial Treatment Planning System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tiwari, P; Chen, Y; Hong, L

2015-06-15

Purpose We developed an automated treatment planning system based on a hierarchical goal programming approach. To demonstrate the feasibility of our method, we report the comparison of prostate treatment plans produced from the automated treatment planning system with those produced by a commercial treatment planning system. Methods In our approach, we prioritized the goals of the optimization, and solved one goal at a time. The purpose of prioritization is to ensure that higher priority dose-volume planning goals are not sacrificed to improve lower priority goals. The algorithm has four steps. The first step optimizes dose to the target structures, whilemore » sparing key sensitive organs from radiation. In the second step, the algorithm finds the best beamlet weight to reduce toxicity risks to normal tissue while holding the objective function achieved in the first step as a constraint, with a small amount of allowed slip. Likewise, the third and fourth steps introduce lower priority normal tissue goals and beam smoothing. We compared with prostate treatment plans from Memorial Sloan Kettering Cancer Center developed using Eclipse, with a prescription dose of 72 Gy. A combination of liear, quadratic, and gEUD objective functions were used with a modified open source solver code (IPOPT). Results Initial plan results on 3 different cases show that the automated planning system is capable of competing or improving on expert-driven eclipse plans. Compared to the Eclipse planning system, the automated system produced up to 26% less mean dose to rectum and 24% less mean dose to bladder while having the same D95 (after matching) to the target. Conclusion We have demonstrated that Pareto optimal treatment plans can be generated automatically without a trial-and-error process. The solver finds an optimal plan for the given patient, as opposed to database-driven approaches that set parameters based on geometry and population modeling.« less

Robust path planning for flexible needle insertion using Markov decision processes.

PubMed

Tan, Xiaoyu; Yu, Pengqian; Lim, Kah-Bin; Chui, Chee-Kong

2018-05-11

Flexible needle has the potential to accurately navigate to a treatment region in the least invasive manner. We propose a new planning method using Markov decision processes (MDPs) for flexible needle navigation that can perform robust path planning and steering under the circumstance of complex tissue-needle interactions. This method enhances the robustness of flexible needle steering from three different perspectives. First, the method considers the problem caused by soft tissue deformation. The method then resolves the common needle penetration failure caused by patterns of targets, while the last solution addresses the uncertainty issues in flexible needle motion due to complex and unpredictable tissue-needle interaction. Computer simulation and phantom experimental results show that the proposed method can perform robust planning and generate a secure control policy for flexible needle steering. Compared with a traditional method using MDPs, the proposed method achieves higher accuracy and probability of success in avoiding obstacles under complicated and uncertain tissue-needle interactions. Future work will involve experiment with biological tissue in vivo. The proposed robust path planning method can securely steer flexible needle within soft phantom tissues and achieve high adaptability in computer simulation.

Vehicle path-planning in three dimensions using optics analogs for optimizing visibility and energy cost

NASA Technical Reports Server (NTRS)

Rowe, Neil C.; Lewis, David H.

1989-01-01

Path planning is an important issue for space robotics. Finding safe and energy-efficient paths in the presence of obstacles and other constraints can be complex although important. High-level (large-scale) path planning for robotic vehicles was investigated in three-dimensional space with obstacles, accounting for: (1) energy costs proportional to path length; (2) turn costs where paths change trajectory abruptly; and (3) safety costs for the danger associated with traversing a particular path due to visibility or invisibility from a fixed set of observers. Paths optimal with respect to these cost factors are found. Autonomous or semi-autonomous vehicles were considered operating either in a space environment around satellites and space platforms, or aircraft, spacecraft, or smart missiles operating just above lunar and planetary surfaces. One class of applications concerns minimizing detection, as for example determining the best way to make complex modifications to a satellite without being observed by hostile sensors; another example is verifying there are no paths (holes) through a space defense system. Another class of applications concerns maximizing detection, as finding a good trajectory between mountain ranges of a planet while staying reasonably close to the surface, or finding paths for a flight between two locations that maximize the average number of triangulation points available at any time along the path.

Sequential quadratic programming-based fast path planning algorithm subject to no-fly zone constraints

NASA Astrophysics Data System (ADS)

Liu, Wei; Ma, Shunjian; Sun, Mingwei; Yi, Haidong; Wang, Zenghui; Chen, Zengqiang

2016-08-01

Path planning plays an important role in aircraft guided systems. Multiple no-fly zones in the flight area make path planning a constrained nonlinear optimization problem. It is necessary to obtain a feasible optimal solution in real time. In this article, the flight path is specified to be composed of alternate line segments and circular arcs, in order to reformulate the problem into a static optimization one in terms of the waypoints. For the commonly used circular and polygonal no-fly zones, geometric conditions are established to determine whether or not the path intersects with them, and these can be readily programmed. Then, the original problem is transformed into a form that can be solved by the sequential quadratic programming method. The solution can be obtained quickly using the Sparse Nonlinear OPTimizer (SNOPT) package. Mathematical simulations are used to verify the effectiveness and rapidity of the proposed algorithm.

AUTOPLAN: A PC-based automated mission planning tool

NASA Technical Reports Server (NTRS)

Paterra, Frank C.; Allen, Marc S.; Lawrence, George F.

1987-01-01

A PC-based automated mission and resource planning tool, AUTOPLAN, is described, with application to small-scale planning and scheduling systems in the Space Station program. The input is a proposed mission profile, including mission duration, number of allowable slip periods, and requirement profiles for one or more resources as a function of time. A corresponding availability profile is also entered for each resource over the whole time interval under study. AUTOPLAN determines all integrated schedules which do not require more than the available resources.

Robot path planning algorithm based on symbolic tags in dynamic environment

NASA Astrophysics Data System (ADS)

Vokhmintsev, A.; Timchenko, M.; Melnikov, A.; Kozko, A.; Makovetskii, A.

2017-09-01

The present work will propose a new heuristic algorithms for path planning of a mobile robot in an unknown dynamic space that have theoretically approved estimates of computational complexity and are approbated for solving specific applied problems.

32. ISOMETRIC VIEW OF PIPING PLAN, SHOWING PATH OF CONDUIT ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

32. ISOMETRIC VIEW OF PIPING PLAN, SHOWING PATH OF CONDUIT FROM CONTROL BUNKER TO SHIELDING TANK. F.C. TORKELSON DRAWING NUMBER 842-ARVFS-701-P-1. INEL INDEX CODE NUMBER: 075 0701 60 851 151977. - Idaho National Engineering Laboratory, Advanced Reentry Vehicle Fusing System, Scoville, Butte County, ID

Real-time path planning in dynamic virtual environments using multiagent navigation graphs.

PubMed

Sud, Avneesh; Andersen, Erik; Curtis, Sean; Lin, Ming C; Manocha, Dinesh

2008-01-01

We present a novel approach for efficient path planning and navigation of multiple virtual agents in complex dynamic scenes. We introduce a new data structure, Multi-agent Navigation Graph (MaNG), which is constructed using first- and second-order Voronoi diagrams. The MaNG is used to perform route planning and proximity computations for each agent in real time. Moreover, we use the path information and proximity relationships for local dynamics computation of each agent by extending a social force model [Helbing05]. We compute the MaNG using graphics hardware and present culling techniques to accelerate the computation. We also address undersampling issues and present techniques to improve the accuracy of our algorithm. Our algorithm is used for real-time multi-agent planning in pursuit-evasion, terrain exploration and crowd simulation scenarios consisting of hundreds of moving agents, each with a distinct goal.

Pep2Path: automated mass spectrometry-guided genome mining of peptidic natural products.

PubMed

Medema, Marnix H; Paalvast, Yared; Nguyen, Don D; Melnik, Alexey; Dorrestein, Pieter C; Takano, Eriko; Breitling, Rainer

2014-09-01

Nonribosomally and ribosomally synthesized bioactive peptides constitute a source of molecules of great biomedical importance, including antibiotics such as penicillin, immunosuppressants such as cyclosporine, and cytostatics such as bleomycin. Recently, an innovative mass-spectrometry-based strategy, peptidogenomics, has been pioneered to effectively mine microbial strains for novel peptidic metabolites. Even though mass-spectrometric peptide detection can be performed quite fast, true high-throughput natural product discovery approaches have still been limited by the inability to rapidly match the identified tandem mass spectra to the gene clusters responsible for the biosynthesis of the corresponding compounds. With Pep2Path, we introduce a software package to fully automate the peptidogenomics approach through the rapid Bayesian probabilistic matching of mass spectra to their corresponding biosynthetic gene clusters. Detailed benchmarking of the method shows that the approach is powerful enough to correctly identify gene clusters even in data sets that consist of hundreds of genomes, which also makes it possible to match compounds from unsequenced organisms to closely related biosynthetic gene clusters in other genomes. Applying Pep2Path to a data set of compounds without known biosynthesis routes, we were able to identify candidate gene clusters for the biosynthesis of five important compounds. Notably, one of these clusters was detected in a genome from a different subphylum of Proteobacteria than that in which the molecule had first been identified. All in all, our approach paves the way towards high-throughput discovery of novel peptidic natural products. Pep2Path is freely available from http://pep2path.sourceforge.net/, implemented in Python, licensed under the GNU General Public License v3 and supported on MS Windows, Linux and Mac OS X.

Project Planning and Reporting

NASA Technical Reports Server (NTRS)

1982-01-01

Project Planning Analysis and Reporting System (PPARS) is automated aid in monitoring and scheduling of activities within project. PPARS system consists of PPARS Batch Program, five preprocessor programs, and two post-processor programs. PPARS Batch program is full CPM (Critical Path Method) scheduling program with resource capabilities. Can process networks with up to 10,000 activities.

A path planning method used in fluid jet polishing eliminating lightweight mirror imprinting effect

NASA Astrophysics Data System (ADS)

Li, Wenzong; Fan, Bin; Shi, Chunyan; Wang, Jia; Zhuo, Bin

2014-08-01

With the development of space technology, the design of optical system tends to large aperture lightweight mirror with high dimension-thickness ratio. However, when the lightweight mirror PV value is less than λ/10 , the surface will show wavy imprinting effect obviously. Imprinting effect introduced by head-tool pressure has become a technological barrier in high-precision lightweight mirror manufacturing. Fluid jet polishing can exclude outside pressure. Presently, machining tracks often used are grating type path, screw type path and pseudo-random path. On the edge of imprinting error, the speed of adjacent path points changes too fast, which causes the machine hard to reflect quickly, brings about new path error, and increases the polishing time due to superfluous path. This paper presents a new planning path method to eliminate imprinting effect. Simulation results show that the path of the improved grating path can better eliminate imprinting effect compared to the general path.

Multi Robot Path Planning for Budgeted Active Perception with Self-Organising Maps

DTIC Science & Technology

2016-10-04

Multi- Robot Path Planning for Budgeted Active Perception with Self-Organising Maps Graeme Best1, Jan Faigl2 and Robert Fitch1 Abstract— We propose a...optimise paths for a multi- robot team that aims to maximally observe a set of nodes in the environment. The selected nodes are observed by visiting...regions, each node has an observation reward, and the robots are constrained by travel budgets. The SOM algorithm jointly selects and allocates nodes

The State of Planning of Automation Projects in the Libraries of Canada.

ERIC Educational Resources Information Center

Clement, Hope E. A.

Library automation in Canada is complicated by the large size, dispersed population, and cultural diversity of the country. The National Library of Canada is actively planning a Canadian library network based on national bibliographic services for which the library is now developing automated systems. Canadian libraries are involved in the…

Autonomous path-planning navigation system for site characterization

NASA Astrophysics Data System (ADS)

Rankin, Arturo L.; Crane, Carl D., III; Armstrong, David G., II; Nease, Allen D.; Brown, H. Edward

1996-05-01

The location and removal of buried munitions is an important yet hazardous task. Current development is aimed at performing both the ordnance location and removal tasks autonomously. An autonomous survey vehicle (ASV) named the Gator has been developed at the Center for Intelligent Machines and Robotics, under the direction of Wright Laboratory, Tyndall Air Force Base, Florida, and the Navy Explosive Ordnance Disposal Technology Division, Indian Head, Maryland. The primary task of the survey vehicle is to autonomously traverse an off-road site, towing behind it a trailer containing a sensor package capable of characterizing the sub-surface contents. Achieving 00 percent coverage of the site is critical to fully characterizing the site. This paper presents a strategy for planning efficient paths for the survey vehicle that guarantees near-complete coverage of a site. A small library of three in-house developed path planners are reviewed. A strategy is also presented to keep the trailer on-path and to calculate the percent of coverage of a site with a resolution of 0.01 m2. All of the algorithms discussed in this paper were initially developed in simulation on a Silicon Graphics computer and subsequently implemented on the survey vehicle.

Task path planning, scheduling and learning for free-ranging robot systems

NASA Technical Reports Server (NTRS)

Wakefield, G. Steve

1987-01-01

The development of robotics applications for space operations is often restricted by the limited movement available to guided robots. Free ranging robots can offer greater flexibility than physically guided robots in these applications. Presented here is an object oriented approach to path planning and task scheduling for free-ranging robots that allows the dynamic determination of paths based on the current environment. The system also provides task learning for repetitive jobs. This approach provides a basis for the design of free-ranging robot systems which are adaptable to various environments and tasks.

Automated VMAT planning for postoperative adjuvant treatment of advanced gastric cancer.

PubMed

Sharfo, Abdul Wahab M; Stieler, Florian; Kupfer, Oskar; Heijmen, Ben J M; Dirkx, Maarten L P; Breedveld, Sebastiaan; Wenz, Frederik; Lohr, Frank; Boda-Heggemann, Judit; Buergy, Daniel

2018-04-23

Postoperative/adjuvant radiotherapy of advanced gastric cancer involves a large planning target volume (PTV) with multi-concave shapes which presents a challenge for volumetric modulated arc therapy (VMAT) planning. This study investigates the advantages of automated VMAT planning for this site compared to manual VMAT planning by expert planners. For 20 gastric cancer patients in the postoperative/adjuvant setting, dual-arc VMAT plans were generated using fully automated multi-criterial treatment planning (autoVMAT), and compared to manually generated VMAT plans (manVMAT). Both automated and manual plans were created to deliver a median dose of 45 Gy to the PTV using identical planning and segmentation parameters. Plans were evaluated by two expert radiation oncologists for clinical acceptability. AutoVMAT and manVMAT plans were also compared based on dose-volume histogram (DVH) and predicted normal tissue complication probability (NTCP) analysis. Both manVMAT and autoVMAT plans were considered clinically acceptable. Target coverage was similar (manVMAT: 96.6 ± 1.6%, autoVMAT: 97.4 ± 1.0%, p = 0.085). With autoVMAT, median kidney dose was reduced on average by > 25%; (for left kidney from 11.3 ± 2.1 Gy to 8.9 ± 3.5 Gy (p = 0.002); for right kidney from 9.2 ± 2.2 Gy to 6.1 ± 1.3 Gy (p <  0.001)). Median dose to the liver was lower as well (18.8 ± 2.3 Gy vs. 17.1 ± 3.6 Gy, p = 0.048). In addition, Dmax of the spinal cord was significantly reduced (38.3 ± 3.7 Gy vs. 31.6 ± 2.6 Gy, p <  0.001). Substantial improvements in dose conformity and integral dose were achieved with autoVMAT plans (4.2% and 9.1%, respectively; p <  0.001). Due to the better OAR sparing in the autoVMAT plans compared to manVMAT plans, the predicted NTCPs for the left and right kidney and the liver-PTV were significantly reduced by 11.3%, 12.8%, 7%, respectively (p ≤ 0.001). Delivery time and total

Transportation planning implications of automated/connected vehicles on Texas highways.

DOT National Transportation Integrated Search

2017-04-01

This research project was focused on the transportation planning implications of automated/connected : vehicles (AV/CVs) on Texas highways. The research assessed how these potentially transformative : technologies can be included in transportation pl...

Results of an Experimental Exploration of Advanced Automated Geospatial Tools: Agility in Complex Planning

DTIC Science & Technology

2009-06-01

AUTOMATED GEOSPATIAL TOOLS : AGILITY IN COMPLEX PLANNING Primary Topic: Track 5 – Experimentation and Analysis Walter A. Powell [STUDENT] - GMU...TITLE AND SUBTITLE Results of an Experimental Exploration of Advanced Automated Geospatial Tools : Agility in Complex Planning 5a. CONTRACT NUMBER...Std Z39-18 Abstract Typically, the development of tools and systems for the military is requirement driven; systems are developed to meet

Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method

NASA Astrophysics Data System (ADS)

McIntosh, Chris; Welch, Mattea; McNiven, Andrea; Jaffray, David A.; Purdie, Thomas G.

2017-08-01

Recent works in automated radiotherapy treatment planning have used machine learning based on historical treatment plans to infer the spatial dose distribution for a novel patient directly from the planning image. We present a probabilistic, atlas-based approach which predicts the dose for novel patients using a set of automatically selected most similar patients (atlases). The output is a spatial dose objective, which specifies the desired dose-per-voxel, and therefore replaces the need to specify and tune dose-volume objectives. Voxel-based dose mimicking optimization then converts the predicted dose distribution to a complete treatment plan with dose calculation using a collapsed cone convolution dose engine. In this study, we investigated automated planning for right-sided oropharaynx head and neck patients treated with IMRT and VMAT. We compare four versions of our dose prediction pipeline using a database of 54 training and 12 independent testing patients by evaluating 14 clinical dose evaluation criteria. Our preliminary results are promising and demonstrate that automated methods can generate comparable dose distributions to clinical. Overall, automated plans achieved an average of 0.6% higher dose for target coverage evaluation criteria, and 2.4% lower dose at the organs at risk criteria levels evaluated compared with clinical. There was no statistically significant difference detected in high-dose conformity between automated and clinical plans as measured by the conformation number. Automated plans achieved nine more unique criteria than clinical across the 12 patients tested and automated plans scored a significantly higher dose at the evaluation limit for two high-risk target coverage criteria and a significantly lower dose in one critical organ maximum dose. The novel dose prediction method with dose mimicking can generate complete treatment plans in 12-13 min without user interaction. It is a promising approach for fully automated treatment

Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method.

PubMed

McIntosh, Chris; Welch, Mattea; McNiven, Andrea; Jaffray, David A; Purdie, Thomas G

2017-07-06

Recent works in automated radiotherapy treatment planning have used machine learning based on historical treatment plans to infer the spatial dose distribution for a novel patient directly from the planning image. We present a probabilistic, atlas-based approach which predicts the dose for novel patients using a set of automatically selected most similar patients (atlases). The output is a spatial dose objective, which specifies the desired dose-per-voxel, and therefore replaces the need to specify and tune dose-volume objectives. Voxel-based dose mimicking optimization then converts the predicted dose distribution to a complete treatment plan with dose calculation using a collapsed cone convolution dose engine. In this study, we investigated automated planning for right-sided oropharaynx head and neck patients treated with IMRT and VMAT. We compare four versions of our dose prediction pipeline using a database of 54 training and 12 independent testing patients by evaluating 14 clinical dose evaluation criteria. Our preliminary results are promising and demonstrate that automated methods can generate comparable dose distributions to clinical. Overall, automated plans achieved an average of 0.6% higher dose for target coverage evaluation criteria, and 2.4% lower dose at the organs at risk criteria levels evaluated compared with clinical. There was no statistically significant difference detected in high-dose conformity between automated and clinical plans as measured by the conformation number. Automated plans achieved nine more unique criteria than clinical across the 12 patients tested and automated plans scored a significantly higher dose at the evaluation limit for two high-risk target coverage criteria and a significantly lower dose in one critical organ maximum dose. The novel dose prediction method with dose mimicking can generate complete treatment plans in 12-13 min without user interaction. It is a promising approach for fully automated treatment

Robot Path Planning in Uncertain Environments: A Language-Measure-Theoretic Approach

DTIC Science & Technology

2015-03-01

in the framework of probabilistic finite state automata (PFSA) and language measure from a control-theoretic perspective. The proposed concept has been...DOI: 10.1115/1.4027876] Keywords: path planning, language measure, probabilistic finite state automata 1 Motivation and Introduction In general

Development and clinical introduction of automated radiotherapy treatment planning for prostate cancer

NASA Astrophysics Data System (ADS)

Winkel, D.; Bol, G. H.; van Asselen, B.; Hes, J.; Scholten, V.; Kerkmeijer, L. G. W.; Raaymakers, B. W.

2016-12-01

To develop an automated radiotherapy treatment planning and optimization workflow to efficiently create patient specifically optimized clinical grade treatment plans for prostate cancer and to implement it in clinical practice. A two-phased planning and optimization workflow was developed to automatically generate 77Gy 5-field simultaneously integrated boost intensity modulated radiation therapy (SIB-IMRT) plans for prostate cancer treatment. A retrospective planning study (n  =  100) was performed in which automatically and manually generated treatment plans were compared. A clinical pilot (n  =  21) was performed to investigate the usability of our method. Operator time for the planning process was reduced to  <5 min. The retrospective planning study showed that 98 plans met all clinical constraints. Significant improvements were made in the volume receiving 72Gy (V72Gy) for the bladder and rectum and the mean dose of the bladder and the body. A reduced plan variance was observed. During the clinical pilot 20 automatically generated plans met all constraints and 17 plans were selected for treatment. The automated radiotherapy treatment planning and optimization workflow is capable of efficiently generating patient specifically optimized and improved clinical grade plans. It has now been adopted as the current standard workflow in our clinic to generate treatment plans for prostate cancer.

The laboratory of the 1990s—Planning for total automation

PubMed Central

Brunner, Linda A.

1992-01-01

The analytical laboratory of the 1990s must be able to meet and accommodate the rapid evolution of modern-day technology. One such area is laboratory automation. Total automation may be seen as the coupling of computerized sample tracking, electronic documentation and data reduction with automated sample handling, preparation and analysis, resulting in a complete analytical procedure with minimal human involvement. Requirements may vary from one laboratory or facility to another, so the automation has to be flexible enough to cover a wide range of applications, and yet fit into specific niches depending on individual needs. Total automation must be planned for, well in advance, if the endeavour is to be a success. Space, laboratory layout, proper equipment, and the availability and access to necessary utilities must be taken into account. Adequate training and experience of the personnel working with the technology must also be ensured. In addition, responsibilities of installation, programming maintenance and operation have to be addressed. Proper time management and the efficient implementation and use of total automation are also crucial to successful operations. This paper provides insights into laboratory organization and requirements, as well as discussing the management issues that must be faced when automating laboratory procedures. PMID:18924925

Development of an automated pre-sampling plan for construction projects : final report.

DOT National Transportation Integrated Search

1983-03-01

The development of an automated pre-sampling plan was undertaken to free the district construction personnel from the cumbersome and time-consuming task of preparing such plans manually. A computer program was written and linked to a data file which ...

A geometrically based method for automated radiosurgery planning.

PubMed

Wagner, T H; Yi, T; Meeks, S L; Bova, F J; Brechner, B L; Chen, Y; Buatti, J M; Friedman, W A; Foote, K D; Bouchet, L G

2000-12-01

A geometrically based method of multiple isocenter linear accelerator radiosurgery treatment planning optimization was developed, based on a target's solid shape. Our method uses an edge detection process to determine the optimal sphere packing arrangement with which to cover the planning target. The sphere packing arrangement is converted into a radiosurgery treatment plan by substituting the isocenter locations and collimator sizes for the spheres. This method is demonstrated on a set of 5 irregularly shaped phantom targets, as well as a set of 10 clinical example cases ranging from simple to very complex in planning difficulty. Using a prototype implementation of the method and standard dosimetric radiosurgery treatment planning tools, feasible treatment plans were developed for each target. The treatment plans generated for the phantom targets showed excellent dose conformity and acceptable dose homogeneity within the target volume. The algorithm was able to generate a radiosurgery plan conforming to the Radiation Therapy Oncology Group (RTOG) guidelines on radiosurgery for every clinical and phantom target examined. This automated planning method can serve as a valuable tool to assist treatment planners in rapidly and consistently designing conformal multiple isocenter radiosurgery treatment plans.

Air Vehicle Path Planning

DTIC Science & Technology

2001-12-13

6-18 6.13. Apollonius Circle for the Case of Two Unequal Power Radars . . . 6-20 6.14. Solution Triangle...Voronoi edge is an Apollonius circle [32, 19]. In this section, we are concerned with the optimality of the Voronoi path for the two radar exposure...Comparison of Cost vs. Path Length for Constrained Trajectories Around and Between Two Radars 6-18 from the two radars is an Apollonius circle

Management Planning for Workplace Automation.

ERIC Educational Resources Information Center

McDole, Thomas L.

Several factors must be considered when implementing office automation. Included among these are whether or not to automate at all, the effects of automation on employees, requirements imposed by automation on the physical environment, effects of automation on the total organization, and effects on clientele. The reasons behind the success or…

Dynamic path planning for autonomous driving on various roads with avoidance of static and moving obstacles

NASA Astrophysics Data System (ADS)

Hu, Xuemin; Chen, Long; Tang, Bo; Cao, Dongpu; He, Haibo

2018-02-01

This paper presents a real-time dynamic path planning method for autonomous driving that avoids both static and moving obstacles. The proposed path planning method determines not only an optimal path, but also the appropriate acceleration and speed for a vehicle. In this method, we first construct a center line from a set of predefined waypoints, which are usually obtained from a lane-level map. A series of path candidates are generated by the arc length and offset to the center line in the s - ρ coordinate system. Then, all of these candidates are converted into Cartesian coordinates. The optimal path is selected considering the total cost of static safety, comfortability, and dynamic safety; meanwhile, the appropriate acceleration and speed for the optimal path are also identified. Various types of roads, including single-lane roads and multi-lane roads with static and moving obstacles, are designed to test the proposed method. The simulation results demonstrate the effectiveness of the proposed method, and indicate its wide practical application to autonomous driving.

Autonomous underwater vehicle adaptive path planning for target classification

NASA Astrophysics Data System (ADS)

Edwards, Joseph R.; Schmidt, Henrik

2002-11-01

Autonomous underwater vehicles (AUVs) are being rapidly developed to carry sensors into the sea in ways that have previously not been possible. The full use of the vehicles, however, is still not near realization due to lack of the true vehicle autonomy that is promised in the label (AUV). AUVs today primarily attempt to follow as closely as possible a preplanned trajectory. The key to increasing the autonomy of the AUV is to provide the vehicle with a means to make decisions based on its sensor receptions. The current work examines the use of active sonar returns from mine-like objects (MLOs) as a basis for sensor-based adaptive path planning, where the path planning objective is to discriminate between real mines and rocks. Once a target is detected in the mine hunting phase, the mine classification phase is initialized with a derivative cost function to emphasize signal differences and enhance classification capability. The AUV moves adaptively to minimize the cost function. The algorithm is verified using at-sea data derived from the joint MIT/SACLANTCEN GOATS experiments and advanced acoustic simulation using SEALAB. The mission oriented operating system (MOOS) real-time simulator is then used to test the onboard implementation of the algorithm.

Automated radiotherapy treatment plan integrity verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang Deshan; Moore, Kevin L.

2012-03-15

Purpose: In our clinic, physicists spend from 15 to 60 min to verify the physical and dosimetric integrity of radiotherapy plans before presentation to radiation oncology physicians for approval. The purpose of this study was to design and implement a framework to automate as many elements of this quality control (QC) step as possible. Methods: A comprehensive computer application was developed to carry out a majority of these verification tasks in the Philips PINNACLE treatment planning system (TPS). This QC tool functions based on both PINNACLE scripting elements and PERL sub-routines. The core of this technique is the method ofmore » dynamic scripting, which involves a PERL programming module that is flexible and powerful for treatment plan data handling. Run-time plan data are collected, saved into temporary files, and analyzed against standard values and predefined logical rules. The results were summarized in a hypertext markup language (HTML) report that is displayed to the user. Results: This tool has been in clinical use for over a year. The occurrence frequency of technical problems, which would cause delays and suboptimal plans, has been reduced since clinical implementation. Conclusions: In addition to drastically reducing the set of human-driven logical comparisons, this QC tool also accomplished some tasks that are otherwise either quite laborious or impractical for humans to verify, e.g., identifying conflicts amongst IMRT optimization objectives.« less

Planning and Resource Management in an Intelligent Automated Power Management System

NASA Technical Reports Server (NTRS)

Morris, Robert A.

1991-01-01

Power system management is a process of guiding a power system towards the objective of continuous supply of electrical power to a set of loads. Spacecraft power system management requires planning and scheduling, since electrical power is a scarce resource in space. The automation of power system management for future spacecraft has been recognized as an important R&D goal. Several automation technologies have emerged including the use of expert systems for automating human problem solving capabilities such as rule based expert system for fault diagnosis and load scheduling. It is questionable whether current generation expert system technology is applicable for power system management in space. The objective of the ADEPTS (ADvanced Electrical Power management Techniques for Space systems) is to study new techniques for power management automation. These techniques involve integrating current expert system technology with that of parallel and distributed computing, as well as a distributed, object-oriented approach to software design. The focus of the current study is the integration of new procedures for automatically planning and scheduling loads with procedures for performing fault diagnosis and control. The objective is the concurrent execution of both sets of tasks on separate transputer processors, thus adding parallelism to the overall management process.

Rapid, parallel path planning by propagating wavefronts of spiking neural activity

PubMed Central

Ponulak, Filip; Hopfield, John J.

2013-01-01

Efficient path planning and navigation is critical for animals, robotics, logistics and transportation. We study a model in which spatial navigation problems can rapidly be solved in the brain by parallel mental exploration of alternative routes using propagating waves of neural activity. A wave of spiking activity propagates through a hippocampus-like network, altering the synaptic connectivity. The resulting vector field of synaptic change then guides a simulated animal to the appropriate selected target locations. We demonstrate that the navigation problem can be solved using realistic, local synaptic plasticity rules during a single passage of a wavefront. Our model can find optimal solutions for competing possible targets or learn and navigate in multiple environments. The model provides a hypothesis on the possible computational mechanisms for optimal path planning in the brain, at the same time it is useful for neuromorphic implementations, where the parallelism of information processing proposed here can fully be harnessed in hardware. PMID:23882213

Optimal path planning for a mobile robot using cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Mohanty, Prases K.; Parhi, Dayal R.

2016-03-01

The shortest/optimal path planning is essential for efficient operation of autonomous vehicles. In this article, a new nature-inspired meta-heuristic algorithm has been applied for mobile robot path planning in an unknown or partially known environment populated by a variety of static obstacles. This meta-heuristic algorithm is based on the levy flight behaviour and brood parasitic behaviour of cuckoos. A new objective function has been formulated between the robots and the target and obstacles, which satisfied the conditions of obstacle avoidance and target-seeking behaviour of robots present in the terrain. Depending upon the objective function value of each nest (cuckoo) in the swarm, the robot avoids obstacles and proceeds towards the target. The smooth optimal trajectory is framed with this algorithm when the robot reaches its goal. Some simulation and experimental results are presented at the end of the paper to show the effectiveness of the proposed navigational controller.

Development of a Software Tool to Automate ADCO Flight Controller Console Planning Tasks

NASA Technical Reports Server (NTRS)

Anderson, Mark G.

2011-01-01

This independent study project covers the development of the International Space Station (ISS) Attitude Determination and Control Officer (ADCO) Planning Exchange APEX Tool. The primary goal of the tool is to streamline existing manual and time-intensive planning tools into a more automated, user-friendly application that interfaces with existing products and allows the ADCO to produce accurate products and timelines more effectively. This paper will survey the current ISS attitude planning process and its associated requirements, goals, documentation and software tools and how a software tool could simplify and automate many of the planning actions which occur at the ADCO console. The project will be covered from inception through the initial prototype delivery in November 2011 and will include development of design requirements and software as well as design verification and testing.

Space station automation and robotics study. Operator-systems interface

NASA Technical Reports Server (NTRS)

1984-01-01

This is the final report of a Space Station Automation and Robotics Planning Study, which was a joint project of the Boeing Aerospace Company, Boeing Commercial Airplane Company, and Boeing Computer Services Company. The study is in support of the Advanced Technology Advisory Committee established by NASA in accordance with a mandate by the U.S. Congress. Boeing support complements that provided to the NASA Contractor study team by four aerospace contractors, the Stanford Research Institute (SRI), and the California Space Institute. This study identifies automation and robotics (A&R) technologies that can be advanced by requirements levied by the Space Station Program. The methodology used in the study is to establish functional requirements for the operator system interface (OSI), establish the technologies needed to meet these requirements, and to forecast the availability of these technologies. The OSI would perform path planning, tracking and control, object recognition, fault detection and correction, and plan modifications in connection with extravehicular (EV) robot operations.

Treatment planning for SBRT using automated field delivery: A case study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ritter, Timothy A., E-mail: timritte@med.umich.edu; Department of Radiation Oncology, Veterans Affairs Ann Arbor Health Care System, Ann Arbor, MI; Owen, Dawn

Stereotactic body radiation therapy (SBRT) treatment planning and delivery can be accomplished using a variety of techniques that achieve highly conformal dose distributions. Herein, we describe a template-based automated treatment field approach that enables rapid delivery of more than 20 coplanar fields. A case study is presented to demonstrate how modest adaptations to traditional SBRT planning can be implemented to take clinical advantage of this technology. Treatment was planned for a left-sided lung lesion adjacent to the chest wall using 25 coplanar treatment fields spaced at 11° intervals. The plan spares the contralateral lung and is in compliance with themore » conformality standards set forth in Radiation Therapy and Oncology Group protocol 0915, and the dose tolerances found in the report of the American Association of Physicists in Medicine Task Group 101. Using a standard template, treatment planning was accomplished in less than 20 minutes, and each 10 Gy fraction was delivered in approximately 5.4 minutes. For those centers equipped with linear accelerators capable of automated treatment field delivery, the use of more than 20 coplanar fields is a viable SBRT planning approach and yields excellent conformality and quality combined with rapid planning and treatment delivery. Although the case study discusses a laterally located lung lesion, this technique can be applied to centrally located tumors with similar results.« less

A two-stage path planning approach for multiple car-like robots based on PH curves and a modified harmony search algorithm

NASA Astrophysics Data System (ADS)

Zeng, Wenhui; Yi, Jin; Rao, Xiao; Zheng, Yun

2017-11-01

In this article, collision-avoidance path planning for multiple car-like robots with variable motion is formulated as a two-stage objective optimization problem minimizing both the total length of all paths and the task's completion time. Accordingly, a new approach based on Pythagorean Hodograph (PH) curves and Modified Harmony Search algorithm is proposed to solve the two-stage path-planning problem subject to kinematic constraints such as velocity, acceleration, and minimum turning radius. First, a method of path planning based on PH curves for a single robot is proposed. Second, a mathematical model of the two-stage path-planning problem for multiple car-like robots with variable motion subject to kinematic constraints is constructed that the first-stage minimizes the total length of all paths and the second-stage minimizes the task's completion time. Finally, a modified harmony search algorithm is applied to solve the two-stage optimization problem. A set of experiments demonstrate the effectiveness of the proposed approach.

Automated replication of cone beam CT-guided treatments in the Pinnacle(3) treatment planning system for adaptive radiotherapy.

PubMed

Hargrave, Catriona; Mason, Nicole; Guidi, Robyn; Miller, Julie-Anne; Becker, Jillian; Moores, Matthew; Mengersen, Kerrie; Poulsen, Michael; Harden, Fiona

2016-03-01

Time-consuming manual methods have been required to register cone-beam computed tomography (CBCT) images with plans in the Pinnacle(3) treatment planning system in order to replicate delivered treatments for adaptive radiotherapy. These methods rely on fiducial marker (FM) placement during CBCT acquisition or the image mid-point to localise the image isocentre. A quality assurance study was conducted to validate an automated CBCT-plan registration method utilising the Digital Imaging and Communications in Medicine (DICOM) Structure Set (RS) and Spatial Registration (RE) files created during online image-guided radiotherapy (IGRT). CBCTs of a phantom were acquired with FMs and predetermined setup errors using various online IGRT workflows. The CBCTs, DICOM RS and RE files were imported into Pinnacle(3) plans of the phantom and the resulting automated CBCT-plan registrations were compared to existing manual methods. A clinical protocol for the automated method was subsequently developed and tested retrospectively using CBCTs and plans for six bladder patients. The automated CBCT-plan registration method was successfully applied to thirty-four phantom CBCT images acquired with an online 0 mm action level workflow. Ten CBCTs acquired with other IGRT workflows required manual workarounds. This was addressed during the development and testing of the clinical protocol using twenty-eight patient CBCTs. The automated CBCT-plan registrations were instantaneous, replicating delivered treatments in Pinnacle(3) with errors of ±0.5 mm. These errors were comparable to mid-point-dependant manual registrations but superior to FM-dependant manual registrations. The automated CBCT-plan registration method quickly and reliably replicates delivered treatments in Pinnacle(3) for adaptive radiotherapy.

Energy-optimal path planning by stochastic dynamically orthogonal level-set optimization

NASA Astrophysics Data System (ADS)

Subramani, Deepak N.; Lermusiaux, Pierre F. J.

2016-04-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. Based on partial differential equations, the methodology rigorously leverages the level-set equation that governs time-optimal reachability fronts for a given relative vehicle-speed function. To set up the energy optimization, the relative vehicle-speed and headings are considered to be stochastic and new stochastic Dynamically Orthogonal (DO) level-set equations are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. Numerical schemes to solve the reduced stochastic DO level-set equations are obtained, and accuracy and efficiency considerations are discussed. These reduced equations are first shown to be efficient at solving the governing stochastic level-sets, in part by comparisons with direct Monte Carlo simulations. To validate the methodology and illustrate its accuracy, comparisons with semi-analytical energy-optimal path solutions are then completed. In particular, we consider the energy-optimal crossing of a canonical steady front and set up its semi-analytical solution using a energy-time nested nonlinear double-optimization scheme. We then showcase the inner workings and nuances of the energy-optimal path planning, considering different mission scenarios. Finally, we study and discuss results of energy-optimal missions in a wind-driven barotropic quasi-geostrophic double-gyre ocean circulation.

Automation for "Direct-to" Clearances in Air-Traffic Control

NASA Technical Reports Server (NTRS)

Erzberger, Heinz; McNally, David

2006-01-01

A method of automation, and a system of computer hardware and software to implement the method, have been invented to assist en-route air-traffic controllers in the issuance of clearances to fly directly to specified waypoints or navigation fixes along straight paths that deviate from previously filed flight plans. Such clearances, called "direct-to" clearances, have been in use since before the invention of this method and system.

Automation of block assignment planning using a diagram-based scenario modeling method

NASA Astrophysics Data System (ADS)

Hwang, In Hyuck; Kim, Youngmin; Lee, Dong Kun; Shin, Jong Gye

2014-03-01

Most shipbuilding scheduling research so far has focused on the load level on the dock plan. This is be¬cause the dock is the least extendable resource in shipyards, and its overloading is difficult to resolve. However, once dock scheduling is completed, making a plan that makes the best use of the rest of the resources in the shipyard to minimize any additional cost is also important. Block assignment planning is one of the midterm planning tasks; it assigns a block to the facility (factory/shop or surface plate) that will actually manufacture the block according to the block characteristics and current situation of the facility. It is one of the most heavily loaded midterm planning tasks and is carried out manu¬ally by experienced workers. In this study, a method of representing the block assignment rules using a diagram was su¬ggested through analysis of the existing manual process. A block allocation program was developed which automated the block assignment process according to the rules represented by the diagram. The planning scenario was validated through a case study that compared the manual assignment and two automated block assignment results.

The automation of remote vehicle control. [in Mars roving vehicles

NASA Technical Reports Server (NTRS)

Paine, G.

1977-01-01

The automation of remote vehicles is becoming necessary to overcome the requirement of having man present as a controller. By removing man, remote vehicles can be operated in areas where the environment is too hostile for man, his reaction times are too slow, time delays are too long, and where his presence is too costly, or where system performance can be improved. This paper addresses the development of automated remote vehicle control for nonspace and space tasks from warehouse vehicles to proposed Mars rovers. The state-of-the-art and the availability of new technology for implementing automated control are reviewed and the major problem areas are outlined. The control strategies are divided into those where the path is planned in advance or constrained, or where the system is a teleoperator, or where automation or robotics have been introduced.

Automated high-dose rate brachytherapy treatment planning for a single-channel vaginal cylinder applicator

NASA Astrophysics Data System (ADS)

Zhou, Yuhong; Klages, Peter; Tan, Jun; Chi, Yujie; Stojadinovic, Strahinja; Yang, Ming; Hrycushko, Brian; Medin, Paul; Pompos, Arnold; Jiang, Steve; Albuquerque, Kevin; Jia, Xun

2017-06-01

High dose rate (HDR) brachytherapy treatment planning is conventionally performed manually and/or with aids of preplanned templates. In general, the standard of care would be elevated by conducting an automated process to improve treatment planning efficiency, eliminate human error, and reduce plan quality variations. Thus, our group is developing AutoBrachy, an automated HDR brachytherapy planning suite of modules used to augment a clinical treatment planning system. This paper describes our proof-of-concept module for vaginal cylinder HDR planning that has been fully developed. After a patient CT scan is acquired, the cylinder applicator is automatically segmented using image-processing techniques. The target CTV is generated based on physician-specified treatment depth and length. Locations of the dose calculation point, apex point and vaginal surface point, as well as the central applicator channel coordinates, and the corresponding dwell positions are determined according to their geometric relationship with the applicator and written to a structure file. Dwell times are computed through iterative quadratic optimization techniques. The planning information is then transferred to the treatment planning system through a DICOM-RT interface. The entire process was tested for nine patients. The AutoBrachy cylindrical applicator module was able to generate treatment plans for these cases with clinical grade quality. Computation times varied between 1 and 3 min on an Intel Xeon CPU E3-1226 v3 processor. All geometric components in the automated treatment plans were generated accurately. The applicator channel tip positions agreed with the manually identified positions with submillimeter deviations and the channel orientations between the plans agreed within less than 1 degree. The automatically generated plans obtained clinically acceptable quality.

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †

PubMed Central

Zhang, Meiyan; Zheng, Yahong Rosa

2017-01-01

This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X−Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem. PMID:28696377

Task Assignment and Path Planning for Multiple Autonomous Underwater Vehicles Using 3D Dubins Curves †.

PubMed

Cai, Wenyu; Zhang, Meiyan; Zheng, Yahong Rosa

2017-07-11

This paper investigates the task assignment and path planning problem for multiple AUVs in three dimensional (3D) underwater wireless sensor networks where nonholonomic motion constraints of underwater AUVs in 3D space are considered. The multi-target task assignment and path planning problem is modeled by the Multiple Traveling Sales Person (MTSP) problem and the Genetic Algorithm (GA) is used to solve the MTSP problem with Euclidean distance as the cost function and the Tour Hop Balance (THB) or Tour Length Balance (TLB) constraints as the stop criterion. The resulting tour sequences are mapped to 2D Dubins curves in the X - Y plane, and then interpolated linearly to obtain the Z coordinates. We demonstrate that the linear interpolation fails to achieve G 1 continuity in the 3D Dubins path for multiple targets. Therefore, the interpolated 3D Dubins curves are checked against the AUV dynamics constraint and the ones satisfying the constraint are accepted to finalize the 3D Dubins curve selection. Simulation results demonstrate that the integration of the 3D Dubins curve with the MTSP model is successful and effective for solving the 3D target assignment and path planning problem.

Integrated optimization of unmanned aerial vehicle task allocation and path planning under steady wind.

PubMed

Luo, He; Liang, Zhengzheng; Zhu, Moning; Hu, Xiaoxuan; Wang, Guoqiang

2018-01-01

Wind has a significant effect on the control of fixed-wing unmanned aerial vehicles (UAVs), resulting in changes in their ground speed and direction, which has an important influence on the results of integrated optimization of UAV task allocation and path planning. The objective of this integrated optimization problem changes from minimizing flight distance to minimizing flight time. In this study, the Euclidean distance between any two targets is expanded to the Dubins path length, considering the minimum turning radius of fixed-wing UAVs. According to the vector relationship between wind speed, UAV airspeed, and UAV ground speed, a method is proposed to calculate the flight time of UAV between targets. On this basis, a variable-speed Dubins path vehicle routing problem (VS-DP-VRP) model is established with the purpose of minimizing the time required for UAVs to visit all the targets and return to the starting point. By designing a crossover operator and mutation operator, the genetic algorithm is used to solve the model, the results of which show that an effective UAV task allocation and path planning solution under steady wind can be provided.

Integrated optimization of unmanned aerial vehicle task allocation and path planning under steady wind

PubMed Central

Liang, Zhengzheng; Zhu, Moning; Hu, Xiaoxuan; Wang, Guoqiang

2018-01-01

Wind has a significant effect on the control of fixed-wing unmanned aerial vehicles (UAVs), resulting in changes in their ground speed and direction, which has an important influence on the results of integrated optimization of UAV task allocation and path planning. The objective of this integrated optimization problem changes from minimizing flight distance to minimizing flight time. In this study, the Euclidean distance between any two targets is expanded to the Dubins path length, considering the minimum turning radius of fixed-wing UAVs. According to the vector relationship between wind speed, UAV airspeed, and UAV ground speed, a method is proposed to calculate the flight time of UAV between targets. On this basis, a variable-speed Dubins path vehicle routing problem (VS-DP-VRP) model is established with the purpose of minimizing the time required for UAVs to visit all the targets and return to the starting point. By designing a crossover operator and mutation operator, the genetic algorithm is used to solve the model, the results of which show that an effective UAV task allocation and path planning solution under steady wind can be provided. PMID:29561888

Sci—Thur PM: Planning and Delivery — 03: Automated delivery and quality assurance of a modulated electron radiation therapy plan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Connell, T; Papaconstadopoulos, P; Alexander, A

2014-08-15

Modulated electron radiation therapy (MERT) offers the potential to improve healthy tissue sparing through increased dose conformity. Challenges remain, however, in accurate beamlet dose calculation, plan optimization, collimation method and delivery accuracy. In this work, we investigate the accuracy and efficiency of an end-to-end MERT plan and automated-delivery workflow for the electron boost portion of a previously treated whole breast irradiation case. Dose calculations were performed using Monte Carlo methods and beam weights were determined using a research-based treatment planning system capable of inverse optimization. The plan was delivered to radiochromic film placed in a water equivalent phantom for verification,more » using an automated motorized tertiary collimator. The automated delivery, which covered 4 electron energies, 196 subfields and 6183 total MU was completed in 25.8 minutes, including 6.2 minutes of beam-on time with the remainder of the delivery time spent on collimator leaf motion and the automated interfacing with the accelerator in service mode. The delivery time could be reduced by 5.3 minutes with minor electron collimator modifications and the beam-on time could be reduced by and estimated factor of 2–3 through redesign of the scattering foils. Comparison of the planned and delivered film dose gave 3%/3 mm gamma pass rates of 62.1, 99.8, 97.8, 98.3, and 98.7 percent for the 9, 12, 16, 20 MeV, and combined energy deliveries respectively. Good results were also seen in the delivery verification performed with a MapCHECK 2 device. The results showed that accurate and efficient MERT delivery is possible with current technologies.« less

Fuzzy logic path planning system for collision avoidance by an autonomous rover vehicle

NASA Technical Reports Server (NTRS)

Murphy, Michael G.

1993-01-01

The Space Exploration Initiative of the United States will make great demands upon NASA and its limited resources. One aspect of great importance will be providing for autonomous (unmanned) operation of vehicles and/or subsystems in space flight and surface exploration. An additional, complicating factor is that much of the need for autonomy of operation will take place under conditions of great uncertainty or ambiguity. Issues in developing an autonomous collision avoidance subsystem within a path planning system for application in a remote, hostile environment that does not lend itself well to remote manipulation by Earth-based telecommunications is addressed. A good focus is unmanned surface exploration of Mars. The uncertainties involved indicate that robust approaches such as fuzzy logic control are particularly appropriate. Four major issues addressed are (1) avoidance of a fuzzy moving obstacle; (2) backoff from a deadend in a static obstacle environment; (3) fusion of sensor data to detect obstacles; and (4) options for adaptive learning in a path planning system. Examples of the need for collision avoidance by an autonomous rover vehicle on the surface of Mars with a moving obstacle would be wind-blown debris, surface flow or anomalies due to subsurface disturbances, another vehicle, etc. The other issues of backoff, sensor fusion, and adaptive learning are important in the overall path planning system.

SU-G-TeP1-05: Development and Clinical Introduction of Automated Radiotherapy Treatment Planning for Prostate Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winkel, D; Bol, GH; Asselen, B van

Purpose: To develop an automated radiotherapy treatment planning and optimization workflow for prostate cancer in order to generate clinical treatment plans. Methods: A fully automated radiotherapy treatment planning and optimization workflow was developed based on the treatment planning system Monaco (Elekta AB, Stockholm, Sweden). To evaluate our method, a retrospective planning study (n=100) was performed on patients treated for prostate cancer with 5 field intensity modulated radiotherapy, receiving a dose of 35×2Gy to the prostate and vesicles and a simultaneous integrated boost of 35×0.2Gy to the prostate only. A comparison was made between the dosimetric values of the automatically andmore » manually generated plans. Operator time to generate a plan and plan efficiency was measured. Results: A comparison of the dosimetric values show that automatically generated plans yield more beneficial dosimetric values. In automatic plans reductions of 43% in the V72Gy of the rectum and 13% in the V72Gy of the bladder are observed when compared to the manually generated plans. Smaller variance in dosimetric values is seen, i.e. the intra- and interplanner variability is decreased. For 97% of the automatically generated plans and 86% of the clinical plans all criteria for target coverage and organs at risk constraints are met. The amount of plan segments and monitor units is reduced by 13% and 9% respectively. Automated planning requires less than one minute of operator time compared to over an hour for manual planning. Conclusion: The automatically generated plans are highly suitable for clinical use. The plans have less variance and a large gain in time efficiency has been achieved. Currently, a pilot study is performed, comparing the preference of the clinician and clinical physicist for the automatic versus manual plan. Future work will include expanding our automated treatment planning method to other tumor sites and develop other automated radiotherapy

Automated Procurement System (APS) revised project management plan (DS-03)

NASA Technical Reports Server (NTRS)

Murphy, Diane R.

1995-01-01

The Project Plan is the governing document for the implementation of the Automated Procurement System (APS). It includes a description of the proposed system, describes the work to be done, establishes a schedule of deliverables, and discusses the major standards and procedures to be followed.

InPRO: Automated Indoor Construction Progress Monitoring Using Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Hamledari, Hesam

In this research, an envisioned automated intelligent robotic solution for automated indoor data collection and inspection that employs a series of unmanned aerial vehicles (UAV), entitled "InPRO", is presented. InPRO consists of four stages, namely: 1) automated path planning; 2) autonomous UAV-based indoor inspection; 3) automated computer vision-based assessment of progress; and, 4) automated updating of 4D building information models (BIM). The works presented in this thesis address the third stage of InPRO. A series of computer vision-based methods that automate the assessment of construction progress using images captured at indoor sites are introduced. The proposed methods employ computer vision and machine learning techniques to detect the components of under-construction indoor partitions. In particular, framing (studs), insulation, electrical outlets, and different states of drywall sheets (installing, plastering, and painting) are automatically detected using digital images. High accuracy rates, real-time performance, and operation without a priori information are indicators of the methods' promising performance.

Adaptive Gait Control for a Quadruped Robot on 3D Path Planning

NASA Astrophysics Data System (ADS)

Igarashi, Hiroshi; Kakikura, Masayoshi

A legged walking robot is able to not only move on irregular terrain but also change its posture. For example, the robot can pass under overhead obstacles by crouching. The purpose of our research is to realize efficient path planning with a quadruped robot. Therefore, the path planning is expected to extended in three dimensions because of the mobility. However, some issues of the quadruped robot, which are instability, workspace limitation, deadlock and slippage, complicate realizing such application. In order to improve these issues and reinforce the mobility, a new static gait pattern for a quadruped robot, called TFG: Trajectory Following Gait, is proposed. The TFG intends to obtain high controllability like a wheel robot. Additionally, the TFG allows to change it posture during the walk. In this paper, some experimental results show that the TFG improves the issues and it is available for efficient locomotion in three dimensional environment.

Constrained VPH+: a local path planning algorithm for a bio-inspired crawling robot with customized ultrasonic scanning sensor.

PubMed

Rao, Akshay; Elara, Mohan Rajesh; Elangovan, Karthikeyan

This paper aims to develop a local path planning algorithm for a bio-inspired, reconfigurable crawling robot. A detailed description of the robotic platform is first provided, and the suitability for deployment of each of the current state-of-the-art local path planners is analyzed after an extensive literature review. The Enhanced Vector Polar Histogram algorithm is described and reformulated to better fit the requirements of the platform. The algorithm is deployed on the robotic platform in crawling configuration and favorably compared with other state-of-the-art local path planning algorithms.

Laser materials processing of complex components: from reverse engineering via automated beam path generation to short process development cycles

NASA Astrophysics Data System (ADS)

Görgl, Richard; Brandstätter, Elmar

2017-01-01

The article presents an overview of what is possible nowadays in the field of laser materials processing. The state of the art in the complete process chain is shown, starting with the generation of a specific components CAD data and continuing with the automated motion path generation for the laser head carried by a CNC or robot system. Application examples from laser cladding and laser-based additive manufacturing are given.

A semi-automated tool for treatment plan-quality evaluation and clinical trial quality assurance

NASA Astrophysics Data System (ADS)

Wang, Jiazhou; Chen, Wenzhou; Studenski, Matthew; Cui, Yunfeng; Lee, Andrew J.; Xiao, Ying

2013-07-01

The goal of this work is to develop a plan-quality evaluation program for clinical routine and multi-institutional clinical trials so that the overall evaluation efficiency is improved. In multi-institutional clinical trials evaluating the plan quality is a time-consuming and labor-intensive process. In this note, we present a semi-automated plan-quality evaluation program which combines MIMVista, Java/MATLAB, and extensible markup language (XML). More specifically, MIMVista is used for data visualization; Java and its powerful function library are implemented for calculating dosimetry parameters; and to improve the clarity of the index definitions, XML is applied. The accuracy and the efficiency of the program were evaluated by comparing the results of the program with the manually recorded results in two RTOG trials. A slight difference of about 0.2% in volume or 0.6 Gy in dose between the semi-automated program and manual recording was observed. According to the criteria of indices, there are minimal differences between the two methods. The evaluation time is reduced from 10-20 min to 2 min by applying the semi-automated plan-quality evaluation program.

ISS Operations Cost Reductions Through Automation of Real-Time Planning Tasks

NASA Technical Reports Server (NTRS)

Hall, Timothy A.; Clancey, William J.; McDonald, Aaron; Toschlog, Jason; Tucker, Tyson; Khan, Ahmed; Madrid, Steven (Eric)

2011-01-01

In 2007 the Johnson Space Center s Mission Operations Directorate (MOD) management team challenged their organizations to find ways to reduce the cost of operations for supporting the International Space Station (ISS) in the Mission Control Center (MCC). Each MOD organization was asked to define and execute projects that would help them attain cost reductions by 2012. The MOD Operations Division Flight Planning Branch responded to this challenge by launching several software automation projects that would allow them to greatly improve console operations and reduce ISS console staffing and intern reduce operating costs. These tasks ranged from improving the management and integration mission plan changes, to automating the uploading and downloading of information to and from the ISS and the associated ground complex tasks that required multiple decision points. The software solutions leveraged several different technologies including customized web applications and implementation of industry standard web services architecture; as well as engaging a previously TRL 4-5 technology developed by Ames Research Center (ARC) that utilized an intelligent agent-based system to manage and automate file traffic flow, archive data, and generate console logs. These projects to date have allowed the MOD Operations organization to remove one full time (7 x 24 x 365) ISS console position in 2010; with the goal of eliminating a second full time ISS console support position by 2012. The team will also reduce one long range planning console position by 2014. When complete, these Flight Planning Branch projects will account for the elimination of 3 console positions and a reduction in staffing of 11 engineering personnel (EP) for ISS.

Completely automated open-path FT-IR spectrometry.

PubMed

Griffiths, Peter R; Shao, Limin; Leytem, April B

2009-01-01

Atmospheric analysis by open-path Fourier-transform infrared (OP/FT-IR) spectrometry has been possible for over two decades but has not been widely used because of the limitations of the software of commercial instruments. In this paper, we describe the current state-of-the-art of the hardware and software that constitutes a contemporary OP/FT-IR spectrometer. We then describe advances that have been made in our laboratory that have enabled many of the limitations of this type of instrument to be overcome. These include not having to acquire a single-beam background spectrum that compensates for absorption features in the spectra of atmospheric water vapor and carbon dioxide. Instead, an easily measured "short path-length" background spectrum is used for calculation of each absorbance spectrum that is measured over a long path-length. To accomplish this goal, the algorithm used to calculate the concentrations of trace atmospheric molecules was changed from classical least-squares regression (CLS) to partial least-squares regression (PLS). For calibration, OP/FT-IR spectra are measured in pristine air over a wide variety of path-lengths, temperatures, and humidities, ratioed against a short-path background, and converted to absorbance; the reference spectrum of each analyte is then multiplied by randomly selected coefficients and added to these background spectra. Automatic baseline correction for small molecules with resolved rotational fine structure, such as ammonia and methane, is effected using wavelet transforms. A novel method of correcting for the effect of the nonlinear response of mercury cadmium telluride detectors is also incorporated. Finally, target factor analysis may be used to detect the onset of a given pollutant when its concentration exceeds a certain threshold. In this way, the concentration of atmospheric species has been obtained from OP/FT-IR spectra measured at intervals of 1 min over a period of many hours with no operator intervention.

Planning collision free paths for two cooperating robots using a divide-and-conquer C-space traversal heuristic

NASA Technical Reports Server (NTRS)

Weaver, Johnathan M.

1993-01-01

A method was developed to plan feasible and obstacle-avoiding paths for two spatial robots working cooperatively in a known static environment. Cooperating spatial robots as referred to herein are robots which work in 6D task space while simultaneously grasping and manipulating a common, rigid payload. The approach is configuration space (c-space) based and performs selective rather than exhaustive c-space mapping. No expensive precomputations are required. A novel, divide-and-conquer type of heuristic is used to guide the selective mapping process. The heuristic does not involve any robot, environment, or task specific assumptions. A technique was also developed which enables solution of the cooperating redundant robot path planning problem without requiring the use of inverse kinematics for a redundant robot. The path planning strategy involves first attempting to traverse along the configuration space vector from the start point towards the goal point. If an unsafe region is encountered, an intermediate via point is identified by conducting a systematic search in the hyperplane orthogonal to and bisecting the unsafe region of the vector. This process is repeatedly applied until a solution to the global path planning problem is obtained. The basic concept behind this strategy is that better local decisions at the beginning of the trouble region may be made if a possible way around the 'center' of the trouble region is known. Thus, rather than attempting paths which look promising locally (at the beginning of a trouble region) but which may not yield overall results, the heuristic attempts local strategies that appear promising for circumventing the unsafe region.

Interactive Learning Environment for Bio-Inspired Optimization Algorithms for UAV Path Planning

ERIC Educational Resources Information Center

Duan, Haibin; Li, Pei; Shi, Yuhui; Zhang, Xiangyin; Sun, Changhao

2015-01-01

This paper describes the development of BOLE, a MATLAB-based interactive learning environment, that facilitates the process of learning bio-inspired optimization algorithms, and that is dedicated exclusively to unmanned aerial vehicle path planning. As a complement to conventional teaching methods, BOLE is designed to help students consolidate the…

Fuzzy Logic Path Planning System for Collision Avoidance by an Autonomous Rover Vehicle

NASA Technical Reports Server (NTRS)

Murphy, Michael G.

1991-01-01

Systems already developed at JSC have shown the benefits of applying fuzzy logic control theory to space related operations. Four major issues are addressed that are associated with developing an autonomous collision avoidance subsystem within a path planning system designed for application in a remote, hostile environment that does not lend itself well to remote manipulation of the vehicle involved through Earth-based telecommunication. A good focus for this is unmanned exploration of the surface of Mars. The uncertainties involved indicate that robust approaches such as fuzzy logic control are particularly appropriate. The four major issues addressed are: (1) avoidance of a single fuzzy moving obstacle; (2) back off from a dead end in a static obstacle environment; (3) fusion of sensor data to detect obstacles; and (4) options for adaptive learning in a path planning system.

Ancient village fire escape path planning based on improved ant colony algorithm

NASA Astrophysics Data System (ADS)

Xia, Wei; Cao, Kang; Hu, QianChuan

2017-06-01

The roadways are narrow and perplexing in ancient villages, it brings challenges and difficulties for people to choose route to escape when a fire occurs. In this paper, a fire escape path planning method based on ant colony algorithm is presented according to the problem. The factors in the fire environment which influence the escape speed is introduced to improve the heuristic function of the algorithm, optimal transfer strategy, and adjustment pheromone volatile factor to improve pheromone update strategy adaptively, improve its dynamic search ability and search speed. Through simulation, the dynamic adjustment of the optimal escape path is obtained, and the method is proved to be feasible.

Three-Dimensional Path Planning for Uninhabited Combat Aerial Vehicle Based on Predator-Prey Pigeon-Inspired Optimization in Dynamic Environment.

PubMed

Zhang, Bo; Duan, Haibin

2017-01-01

Three-dimension path planning of uninhabited combat aerial vehicle (UCAV) is a complicated optimal problem, which mainly focused on optimizing the flight route considering the different types of constrains under complex combating environment. A novel predator-prey pigeon-inspired optimization (PPPIO) is proposed to solve the UCAV three-dimension path planning problem in dynamic environment. Pigeon-inspired optimization (PIO) is a new bio-inspired optimization algorithm. In this algorithm, map and compass operator model and landmark operator model are used to search the best result of a function. The prey-predator concept is adopted to improve global best properties and enhance the convergence speed. The characteristics of the optimal path are presented in the form of a cost function. The comparative simulation results show that our proposed PPPIO algorithm is more efficient than the basic PIO, particle swarm optimization (PSO), and different evolution (DE) in solving UCAV three-dimensional path planning problems.

Validation of Fully Automated VMAT Plan Generation for Library-Based Plan-of-the-Day Cervical Cancer Radiotherapy

PubMed Central

Breedveld, Sebastiaan; Voet, Peter W. J.; Heijkoop, Sabrina T.; Mens, Jan-Willem M.; Hoogeman, Mischa S.; Heijmen, Ben J. M.

2016-01-01

Purpose To develop and validate fully automated generation of VMAT plan-libraries for plan-of-the-day adaptive radiotherapy in locally-advanced cervical cancer. Material and Methods Our framework for fully automated treatment plan generation (Erasmus-iCycle) was adapted to create dual-arc VMAT treatment plan libraries for cervical cancer patients. For each of 34 patients, automatically generated VMAT plans (autoVMAT) were compared to manually generated, clinically delivered 9-beam IMRT plans (CLINICAL), and to dual-arc VMAT plans generated manually by an expert planner (manVMAT). Furthermore, all plans were benchmarked against 20-beam equi-angular IMRT plans (autoIMRT). For all plans, a PTV coverage of 99.5% by at least 95% of the prescribed dose (46 Gy) had the highest planning priority, followed by minimization of V45Gy for small bowel (SB). Other OARs considered were bladder, rectum, and sigmoid. Results All plans had a highly similar PTV coverage, within the clinical constraints (above). After plan normalizations for exactly equal median PTV doses in corresponding plans, all evaluated OAR parameters in autoVMAT plans were on average lower than in the CLINICAL plans with an average reduction in SB V45Gy of 34.6% (p<0.001). For 41/44 autoVMAT plans, SB V45Gy was lower than for manVMAT (p<0.001, average reduction 30.3%), while SB V15Gy increased by 2.3% (p = 0.011). AutoIMRT reduced SB V45Gy by another 2.7% compared to autoVMAT, while also resulting in a 9.0% reduction in SB V15Gy (p<0.001), but with a prolonged delivery time. Differences between manVMAT and autoVMAT in bladder, rectal and sigmoid doses were ≤ 1%. Improvements in SB dose delivery with autoVMAT instead of manVMAT were higher for empty bladder PTVs compared to full bladder PTVs, due to differences in concavity of the PTVs. Conclusions Quality of automatically generated VMAT plans was superior to manually generated plans. Automatic VMAT plan generation for cervical cancer has been implemented in

Validation of Fully Automated VMAT Plan Generation for Library-Based Plan-of-the-Day Cervical Cancer Radiotherapy.

PubMed

Sharfo, Abdul Wahab M; Breedveld, Sebastiaan; Voet, Peter W J; Heijkoop, Sabrina T; Mens, Jan-Willem M; Hoogeman, Mischa S; Heijmen, Ben J M

2016-01-01

To develop and validate fully automated generation of VMAT plan-libraries for plan-of-the-day adaptive radiotherapy in locally-advanced cervical cancer. Our framework for fully automated treatment plan generation (Erasmus-iCycle) was adapted to create dual-arc VMAT treatment plan libraries for cervical cancer patients. For each of 34 patients, automatically generated VMAT plans (autoVMAT) were compared to manually generated, clinically delivered 9-beam IMRT plans (CLINICAL), and to dual-arc VMAT plans generated manually by an expert planner (manVMAT). Furthermore, all plans were benchmarked against 20-beam equi-angular IMRT plans (autoIMRT). For all plans, a PTV coverage of 99.5% by at least 95% of the prescribed dose (46 Gy) had the highest planning priority, followed by minimization of V45Gy for small bowel (SB). Other OARs considered were bladder, rectum, and sigmoid. All plans had a highly similar PTV coverage, within the clinical constraints (above). After plan normalizations for exactly equal median PTV doses in corresponding plans, all evaluated OAR parameters in autoVMAT plans were on average lower than in the CLINICAL plans with an average reduction in SB V45Gy of 34.6% (p<0.001). For 41/44 autoVMAT plans, SB V45Gy was lower than for manVMAT (p<0.001, average reduction 30.3%), while SB V15Gy increased by 2.3% (p = 0.011). AutoIMRT reduced SB V45Gy by another 2.7% compared to autoVMAT, while also resulting in a 9.0% reduction in SB V15Gy (p<0.001), but with a prolonged delivery time. Differences between manVMAT and autoVMAT in bladder, rectal and sigmoid doses were ≤ 1%. Improvements in SB dose delivery with autoVMAT instead of manVMAT were higher for empty bladder PTVs compared to full bladder PTVs, due to differences in concavity of the PTVs. Quality of automatically generated VMAT plans was superior to manually generated plans. Automatic VMAT plan generation for cervical cancer has been implemented in our clinical routine. Due to the achieved workload

A global approach to kinematic path planning to robots with holonomic and nonholonomic constraints

NASA Technical Reports Server (NTRS)

Divelbiss, Adam; Seereeram, Sanjeev; Wen, John T.

1993-01-01

Robots in applications may be subject to holonomic or nonholonomic constraints. Examples of holonomic constraints include a manipulator constrained through the contact with the environment, e.g., inserting a part, turning a crank, etc., and multiple manipulators constrained through a common payload. Examples of nonholonomic constraints include no-slip constraints on mobile robot wheels, local normal rotation constraints for soft finger and rolling contacts in grasping, and conservation of angular momentum of in-orbit space robots. The above examples all involve equality constraints; in applications, there are usually additional inequality constraints such as robot joint limits, self collision and environment collision avoidance constraints, steering angle constraints in mobile robots, etc. The problem of finding a kinematically feasible path that satisfies a given set of holonomic and nonholonomic constraints, of both equality and inequality types is addressed. The path planning problem is first posed as a finite time nonlinear control problem. This problem is subsequently transformed to a static root finding problem in an augmented space which can then be iteratively solved. The algorithm has shown promising results in planning feasible paths for redundant arms satisfying Cartesian path following and goal endpoint specifications, and mobile vehicles with multiple trailers. In contrast to local approaches, this algorithm is less prone to problems such as singularities and local minima.

Path planning for persistent surveillance applications using fixed-wing unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Keller, James F.

This thesis addresses coordinated path planning for fixed-wing Unmanned Aerial Vehicles (UAVs) engaged in persistent surveillance missions. While uniquely suited to this mission, fixed wing vehicles have maneuver constraints that can limit their performance in this role. Current technology vehicles are capable of long duration flight with a minimal acoustic footprint while carrying an array of cameras and sensors. Both military tactical and civilian safety applications can benefit from this technology. We make three main contributions: C1 A sequential path planner that generates a C 2 flight plan to persistently acquire a covering set of data over a user designated area of interest. The planner features the following innovations: • A path length abstraction that embeds kino-dynamic motion constraints to estimate feasible path length. • A Traveling Salesman-type planner to generate a covering set route based on the path length abstraction. • A smooth path generator that provides C 2 routes that satisfy user specified curvature constraints. C2 A set of algorithms to coordinate multiple UAVs, including mission commencement from arbitrary locations to the start of a coordinated mission and de-confliction of paths to avoid collisions with other vehicles and fixed obstacles. C3 A numerically robust toolbox of spline-based algorithms tailored for vehicle routing validated through flight test experiments on multiple platforms. A variety of tests and platforms are discussed. The algorithms presented are based on a technical approach with approximately equal emphasis on analysis, computation, dynamic simulation, and flight test experimentation. Our planner (C1) directly takes into account vehicle maneuverability and agility constraints that could otherwise render simple solutions infeasible. This is especially important when surveillance objectives elevate the importance of optimized paths. Researchers have developed a diverse range of solutions for persistent

Implications of path tolerance and path characteristics on critical vehicle manoeuvres

NASA Astrophysics Data System (ADS)

Lundahl, K.; Frisk, E.; Nielsen, L.

2017-12-01

Path planning and path following are core components in safe autonomous driving. Typically, a path planner provides a path with some tolerance on how tightly the path should be followed. Based on that, and other path characteristics, for example, sharpness of curves, a speed profile needs to be assigned so that the vehicle can stay within the given tolerance without going unnecessarily slow. Here, such trajectory planning is based on optimal control formulations where critical cases arise as on-the-limit solutions. The study focuses on heavy commercial vehicles, causing rollover to be of a major concern, due to the relatively high centre of gravity. Several results are obtained on required model complexity depending on path characteristics, for example, quantification of required path tolerance for a simple model to be sufficient, quantification of when yaw inertia needs to be considered in more detail, and how the curvature rate of change interplays with available friction. Overall, in situations where the vehicle is subject to a wide range of driving conditions, from good transport roads to more tricky avoidance manoeuvres, the requirements on the path following will vary. For this, the provided results form a basis for real-time path following.

Study of Double-Weighted Graph Model and Optimal Path Planning for Tourist Scenic Area Oriented Intelligent Tour Guide

NASA Astrophysics Data System (ADS)

Shi, Y.; Long, Y.; Wi, X. L.

2014-04-01

When tourists visiting multiple tourist scenic spots, the travel line is usually the most effective road network according to the actual tour process, and maybe the travel line is different from planned travel line. For in the field of navigation, a proposed travel line is normally generated automatically by path planning algorithm, considering the scenic spots' positions and road networks. But when a scenic spot have a certain area and have multiple entrances or exits, the traditional described mechanism of single point coordinates is difficult to reflect these own structural features. In order to solve this problem, this paper focuses on the influence on the process of path planning caused by scenic spots' own structural features such as multiple entrances or exits, and then proposes a doubleweighted Graph Model, for the weight of both vertexes and edges of proposed Model can be selected dynamically. And then discusses the model building method, and the optimal path planning algorithm based on Dijkstra algorithm and Prim algorithm. Experimental results show that the optimal planned travel line derived from the proposed model and algorithm is more reasonable, and the travelling order and distance would be further optimized.

Path planning for robotic truss assembly

NASA Technical Reports Server (NTRS)

Sanderson, Arthur C.

1993-01-01

A new Potential Fields approach to the robotic path planning problem is proposed and implemented. Our approach, which is based on one originally proposed by Munger, computes an incremental joint vector based upon attraction to a goal and repulsion from obstacles. By repetitively adding and computing these 'steps', it is hoped (but not guaranteed) that the robot will reach its goal. An attractive force exerted by the goal is found by solving for the the minimum norm solution to the linear Jacobian equation. A repulsive force between obstacles and the robot's links is used to avoid collisions. Its magnitude is inversely proportional to the distance. Together, these forces make the goal the global minimum potential point, but local minima can stop the robot from ever reaching that point. Our approach improves on a basic, potential field paradigm developed by Munger by using an active, adaptive field - what we will call a 'flexible' potential field. Active fields are stronger when objects move towards one another and weaker when they move apart. An adaptive field's strength is individually tailored to be just strong enough to avoid any collision. In addition to the local planner, a global planning algorithm helps the planner to avoid local field minima by providing subgoals. These subgoals are based on the obstacles which caused the local planner to fail. A best-first search algorithm A* is used for graph search.

Path Planning Based on Ply Orientation Information for Automatic Fiber Placement on Mesh Surface

NASA Astrophysics Data System (ADS)

Pei, Jiazhi; Wang, Xiaoping; Pei, Jingyu; Yang, Yang

2018-03-01

This article introduces an investigation of path planning with ply orientation information for automatic fiber placement (AFP) on open-contoured mesh surface. The new method makes use of the ply orientation information generated by loading characteristics on surface, divides the surface into several zones according to the ply orientation information and then designs different fiber paths in different zones. This article also gives new idea of up-layer design in order to make up for defects between parts and improve product's strength.

Improving the Operations of the Earth Observing One Mission via Automated Mission Planning

NASA Technical Reports Server (NTRS)

Chien, Steve A.; Tran, Daniel; Rabideau, Gregg; Schaffer, Steve; Mandl, Daniel; Frye, Stuart

2010-01-01

We describe the modeling and reasoning about operations constraints in an automated mission planning system for an earth observing satellite - EO-1. We first discuss the large number of elements that can be naturally represented in an expressive planning and scheduling framework. We then describe a number of constraints that challenge the current state of the art in automated planning systems and discuss how we modeled these constraints as well as discuss tradeoffs in representation versus efficiency. Finally we describe the challenges in efficiently generating operations plans for this mission. These discussions involve lessons learned from an operations model that has been in use since Fall 2004 (called R4) as well as a newer more accurate operations model operational since June 2009 (called R5). We present analysis of the R5 software documenting a significant (greater than 50%) increase in the number of weekly observations scheduled by the EO-1 mission. We also show that the R5 mission planning system produces schedules within 15% of an upper bound on optimal schedules. This operational enhancement has created value of millions of dollars US over the projected remaining lifetime of the EO-1 mission.

Toward Shared Working Space of Human and Robotic Agents Through Dipole Flow Field for Dependable Path Planning.

PubMed

Trinh, Lan Anh; Ekström, Mikael; Cürüklü, Baran

2018-01-01

Recent industrial developments in autonomous systems, or agents, which assume that humans and the agents share the same space or even work in close proximity, open for new challenges in robotics, especially in motion planning and control. In these settings, the control system should be able to provide these agents a reliable path following control when they are working in a group or in collaboration with one or several humans in complex and dynamic environments. In such scenarios, these agents are not only moving to reach their goals, i.e., locations, they are also aware of the movements of other entities to find a collision-free path. Thus, this paper proposes a dependable, i.e., safe, reliable and effective, path planning algorithm for a group of agents that share their working space with humans. Firstly, the method employs the Theta * algorithm to initialize the paths from a starting point to a goal for a set of agents. As Theta * algorithm is computationally heavy, it only reruns when there is a significant change of the environment. To deal with the movements of the agents, a static flow field along the configured path is defined. This field is used by the agents to navigate and reach their goals even if the planned trajectories are changed. Secondly, a dipole field is calculated to avoid the collision of agents with other agents and human subjects. In this approach, each agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. The effectiveness of the proposed approach has been evaluated with extensive simulations. The results show that the static flow field is able to drive agents to the goals with a small number of requirements to update the path of agents. Meanwhile, the dipole flow field plays an important role to prevent collisions. The combination of

Robot Path Planning in Uncertain Environments: A Language Measure-theoretic Approach

DTIC Science & Technology

2014-01-01

Paper DS-14-1028 to appear in the Special Issue on Stochastic Models, Control and Algorithms in Robotics, ASME Journal of Dynamic Systems...Measurement and Control Robot Path Planning in Uncertain Environments: A Language Measure-theoretic Approach⋆ Devesh K. Jha† Yue Li† Thomas A. Wettergren‡† Asok...algorithm, called ν⋆, that was formulated in the framework of probabilistic finite state automata (PFSA) and language measure from a control -theoretic

Lung fissure detection in CT images using global minimal paths

NASA Astrophysics Data System (ADS)

Appia, Vikram; Patil, Uday; Das, Bipul

2010-03-01

Pulmonary fissures separate human lungs into five distinct regions called lobes. Detection of fissure is essential for localization of the lobar distribution of lung diseases, surgical planning and follow-up. Treatment planning also requires calculation of the lobe volume. This volume estimation mandates accurate segmentation of the fissures. Presence of other structures (like vessels) near the fissure, along with its high variational probability in terms of position, shape etc. makes the lobe segmentation a challenging task. Also, false incomplete fissures and occurrence of diseases add to the complications of fissure detection. In this paper, we propose a semi-automated fissure segmentation algorithm using a minimal path approach on CT images. An energy function is defined such that the path integral over the fissure is the global minimum. Based on a few user defined points on a single slice of the CT image, the proposed algorithm minimizes a 2D energy function on the sagital slice computed using (a) intensity (b) distance of the vasculature, (c) curvature in 2D, (d) continuity in 3D. The fissure is the infimum energy path between a representative point on the fissure and nearest lung boundary point in this energy domain. The algorithm has been tested on 10 CT volume datasets acquired from GE scanners at multiple clinical sites. The datasets span through different pathological conditions and varying imaging artifacts.

Planning minimum-energy paths in an off-road environment with anisotropic traversal costs and motion constraints. Doctoral thesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ross, R.S.

1989-06-01

For a vehicle operating across arbitrarily-contoured terrain, finding the most fuel-efficient route between two points can be viewed as a high-level global path-planning problem with traversal costs and stability dependent on the direction of travel (anisotropic). The problem assumes a two-dimensional polygonal map of homogeneous cost regions for terrain representation constructed from elevation information. The anisotropic energy cost of vehicle motion has a non-braking component dependent on horizontal distance, a braking component dependent on vertical distance, and a constant path-independent component. The behavior of minimum-energy paths is then proved to be restricted to a small, but optimal set of traversalmore » types. An optimal-path-planning algorithm, using a heuristic search technique, reduces the infinite number of paths between the start and goal points to a finite number by generating sequences of goal-feasible window lists from analyzing the polygonal map and applying pruning criteria. The pruning criteria consist of visibility analysis, heading analysis, and region-boundary constraints. Each goal-feasible window lists specifies an associated convex optimization problem, and the best of all locally-optimal paths through the goal-feasible window lists is the globally-optimal path. These ideas have been implemented in a computer program, with results showing considerably better performance than the exponential average-case behavior predicted.« less

Integrated Flight Path Planning System and Flight Control System for Unmanned Helicopters

PubMed Central

Jan, Shau Shiun; Lin, Yu Hsiang

2011-01-01

This paper focuses on the design of an integrated navigation and guidance system for unmanned helicopters. The integrated navigation system comprises two systems: the Flight Path Planning System (FPPS) and the Flight Control System (FCS). The FPPS finds the shortest flight path by the A-Star (A*) algorithm in an adaptive manner for different flight conditions, and the FPPS can add a forbidden zone to stop the unmanned helicopter from crossing over into dangerous areas. In this paper, the FPPS computation time is reduced by the multi-resolution scheme, and the flight path quality is improved by the path smoothing methods. Meanwhile, the FCS includes the fuzzy inference systems (FISs) based on the fuzzy logic. By using expert knowledge and experience to train the FIS, the controller can operate the unmanned helicopter without dynamic models. The integrated system of the FPPS and the FCS is aimed at providing navigation and guidance to the mission destination and it is implemented by coupling the flight simulation software, X-Plane, and the computing software, MATLAB. Simulations are performed and shown in real time three-dimensional animations. Finally, the integrated system is demonstrated to work successfully in controlling the unmanned helicopter to operate in various terrains of a digital elevation model (DEM). PMID:22164029

Integrated flight path planning system and flight control system for unmanned helicopters.

PubMed

Jan, Shau Shiun; Lin, Yu Hsiang

2011-01-01

This paper focuses on the design of an integrated navigation and guidance system for unmanned helicopters. The integrated navigation system comprises two systems: the Flight Path Planning System (FPPS) and the Flight Control System (FCS). The FPPS finds the shortest flight path by the A-Star (A*) algorithm in an adaptive manner for different flight conditions, and the FPPS can add a forbidden zone to stop the unmanned helicopter from crossing over into dangerous areas. In this paper, the FPPS computation time is reduced by the multi-resolution scheme, and the flight path quality is improved by the path smoothing methods. Meanwhile, the FCS includes the fuzzy inference systems (FISs) based on the fuzzy logic. By using expert knowledge and experience to train the FIS, the controller can operate the unmanned helicopter without dynamic models. The integrated system of the FPPS and the FCS is aimed at providing navigation and guidance to the mission destination and it is implemented by coupling the flight simulation software, X-Plane, and the computing software, MATLAB. Simulations are performed and shown in real time three-dimensional animations. Finally, the integrated system is demonstrated to work successfully in controlling the unmanned helicopter to operate in various terrains of a digital elevation model (DEM).

Automated IMRT planning in Pinnacle : A study in head-and-neck cancer.

PubMed

Kusters, J M A M; Bzdusek, K; Kumar, P; van Kollenburg, P G M; Kunze-Busch, M C; Wendling, M; Dijkema, T; Kaanders, J H A M

2017-12-01

This study evaluates the performance and planning efficacy of the Auto-Planning (AP) module in the clinical version of Pinnacle 9.10 (Philips Radiation Oncology Systems, Fitchburg, WI, USA). Twenty automated intensity-modulated radiotherapy (IMRT) plans were compared with the original manually planned clinical IMRT plans from patients with oropharyngeal cancer. Auto-Planning with IMRT offers similar coverage of the planning target volume as the original manually planned clinical plans, as well as better sparing of the contralateral parotid gland, contralateral submandibular gland, larynx, mandible, and brainstem. The mean dose of the contralateral parotid gland and contralateral submandibular gland could be reduced by 2.5 Gy and 1.7 Gy on average. The number of monitor units was reduced with an average of 143.9 (18%). Hands-on planning time was reduced from 1.5-3 h to less than 1 h. The Auto-Planning module was able to produce clinically acceptable head and neck IMRT plans with consistent quality.

Path Planning for Non-Circular, Non-Holonomic Robots in Highly Cluttered Environments.

PubMed

Samaniego, Ricardo; Lopez, Joaquin; Vazquez, Fernando

2017-08-15

This paper presents an algorithm for finding a solution to the problem of planning a feasible path for a slender autonomous mobile robot in a large and cluttered environment. The presented approach is based on performing a graph search on a kinodynamic-feasible lattice state space of high resolution; however, the technique is applicable to many search algorithms. With the purpose of allowing the algorithm to consider paths that take the robot through narrow passes and close to obstacles, high resolutions are used for the lattice space and the control set. This introduces new challenges because one of the most computationally expensive parts of path search based planning algorithms is calculating the cost of each one of the actions or steps that could potentially be part of the trajectory. The reason for this is that the evaluation of each one of these actions involves convolving the robot's footprint with a portion of a local map to evaluate the possibility of a collision, an operation that grows exponentially as the resolution is increased. The novel approach presented here reduces the need for these convolutions by using a set of offline precomputed maps that are updated, by means of a partial convolution, as new information arrives from sensors or other sources. Not only does this improve run-time performance, but it also provides support for dynamic search in changing environments. A set of alternative fast convolution methods are also proposed, depending on whether the environment is cluttered with obstacles or not. Finally, we provide both theoretical and experimental results from different experiments and applications.

Probabilistic Path Planning of Montgolfier Balloons in Strong, Uncertain Wind Fields

NASA Technical Reports Server (NTRS)

Wolf, Michael; Blackmore, James C.; Kuwata, Yoshiaki

2011-01-01

Lighter-than-air vehicles such as hot-air balloons have been proposed for exploring Saturn s moon Titan, as well as other bodies with significant atmospheres. For these vehicles to navigate effectively, it is critical to incorporate the effects of surrounding wind fields, especially as these winds will likely be strong relative to the control authority of the vehicle. Predictive models of these wind fields are available, and previous research has considered problems of planning paths subject to these predicted forces. However, such previous work has considered the wind fields as known a priori, whereas in practical applications, the actual wind vector field is not known exactly and may deviate significantly from the wind velocities estimated by the model. A probabilistic 3D path-planning algorithm was developed for balloons to use uncertain wind models to generate time-efficient paths. The nominal goal of the algorithm is to determine what altitude and what horizontal actuation, if any is available on the vehicle, to use to reach a particular goal location in the least expected time, utilizing advantageous winds. The solution also enables one to quickly evaluate the expected time-to-goal from any other location and to avoid regions of large uncertainty. This method is designed for balloons in wind fields but may be generalized for any buoyant vehicle operating in a vector field. To prepare the planning problem, the uncertainty in the wind field is modeled. Then, the problem of reaching a particular goal location is formulated as a Markov decision process (MDP) using a discretized space approach. Solving the MDP provides a policy of what actuation option (how much buoyancy change and, if applicable, horizontal actuation) should be selected at any given location to minimize the expected time-to-goal. The results provide expected time-to-goal values from any given location on the globe in addition to the action policy. This stochastic approach can also provide

Asset - An application in mission automation for science planning

NASA Technical Reports Server (NTRS)

Finnerty, D. F.; Martin, J.; Doms, P. E.

1987-01-01

Recent advances in computer technology were used to great advantage in planning science observation sequences for the Voyager 2 encounter with Uranus in 1986. Despite a loss of experienced personnel, a challenging schedule, workforce limitations, and the complex nature of the Uranus encounter itself, the resultant science observation timelines were the most highly optimized of the five Voyager encounters with the outer planets. In part, this was due to the development of a microcomputer-based system, called ASSET (Automated Science Sequence Encounter Timelines generator), which was used to design those science observation timelines. This paper details the development of that system. ASSET demonstrates several features essential to the design of the first expert systems for science planning which will be applied for future missions.

Automated Data Assimilation and Flight Planning for Multi-Platform Observation Missions

NASA Technical Reports Server (NTRS)

Oza, Nikunj; Morris, Robert A.; Strawa, Anthony; Kurklu, Elif; Keely, Leslie

2008-01-01

This is a progress report on an effort in which our goal is to demonstrate the effectiveness of automated data mining and planning for the daily management of Earth Science missions. Currently, data mining and machine learning technologies are being used by scientists at research labs for validating Earth science models. However, few if any of these advanced techniques are currently being integrated into daily mission operations. Consequently, there are significant gaps in the knowledge that can be derived from the models and data that are used each day for guiding mission activities. The result can be sub-optimal observation plans, lack of useful data, and wasteful use of resources. Recent advances in data mining, machine learning, and planning make it feasible to migrate these technologies into the daily mission planning cycle. We describe the design of a closed loop system for data acquisition, processing, and flight planning that integrates the results of machine learning into the flight planning process.

Optimal Paths in Gliding Flight

NASA Astrophysics Data System (ADS)

Wolek, Artur

Underwater gliders are robust and long endurance ocean sampling platforms that are increasingly being deployed in coastal regions. This new environment is characterized by shallow waters and significant currents that can challenge the mobility of these efficient (but traditionally slow moving) vehicles. This dissertation aims to improve the performance of shallow water underwater gliders through path planning. The path planning problem is formulated for a dynamic particle (or "kinematic car") model. The objective is to identify the path which satisfies specified boundary conditions and minimizes a particular cost. Several cost functions are considered. The problem is addressed using optimal control theory. The length scales of interest for path planning are within a few turn radii. First, an approach is developed for planning minimum-time paths, for a fixed speed glider, that are sub-optimal but are guaranteed to be feasible in the presence of unknown time-varying currents. Next the minimum-time problem for a glider with speed controls, that may vary between the stall speed and the maximum speed, is solved. Last, optimal paths that minimize change in depth (equivalently, maximize range) are investigated. Recognizing that path planning alone cannot overcome all of the challenges associated with significant currents and shallow waters, the design of a novel underwater glider with improved capabilities is explored. A glider with a pneumatic buoyancy engine (allowing large, rapid buoyancy changes) and a cylindrical moving mass mechanism (generating large pitch and roll moments) is designed, manufactured, and tested to demonstrate potential improvements in speed and maneuverability.

A Path Planning and Obstacle Avoidance Hybrid System Using a Connectionist Network

DTIC Science & Technology

1990-06-01

Department lele7 Prfessor of Aerospace Sciences and Mathematical Sciences Houston, Texas June, 1990 Abstract A PATH PLANNING AND OBSTACLE AVOIDANCE HYBRID...See Weiland (1989), Wu (1989), Norwood (1989), Cheatham (1987 & 1989), Adnan (1990), and Regalbuto (1988 & 1990).] Possible applications of this...neuron model’s output can be described mathematically as: Yj(t+ At) =sgn ijXi(t)-O Other non-linearity functions, such as and the sigmoid/ logistics

The intertwining paths of the density managment and riparian buffer study and the Northwest Forest Plan

Treesearch

Kenneth J. Ruzicka; Deanna H. Olson; Klaus J. Puettmann

2013-01-01

Initiated simultaneously, the Density Management and Riparian Buff er Study of western Oregon and the Northwest Forest Plan have had intertwining paths related to federal forest management and policy changes in the Pacifi c Northwest over the last 15 to 20 years. We briefl y discuss the development of the Northwest Forest Plan and how it changed the way forest policy...

Lagrangian coherent structure assisted path planning for transoceanic autonomous underwater vehicle missions.

PubMed

Ramos, A G; García-Garrido, V J; Mancho, A M; Wiggins, S; Coca, J; Glenn, S; Schofield, O; Kohut, J; Aragon, D; Kerfoot, J; Haskins, T; Miles, T; Haldeman, C; Strandskov, N; Allsup, B; Jones, C; Shapiro, J

2018-03-15

Transoceanic Gliders are Autonomous Underwater Vehicles (AUVs) for which there is a developing and expanding range of applications in open-seas research, technology and underwater clean transport. Mature glider autonomy, operating depth (0-1000 meters) and low energy consumption without a CO 2 footprint enable evolutionary access across ocean basins. Pursuant to the first successful transatlantic glider crossing in December 2009, the Challenger Mission has opened the door to long-term, long-distance routine transoceanic AUV missions. These vehicles, which glide through the water column between 0 and 1000 meters depth, are highly sensitive to the ocean current field. Consequently, it is essential to exploit the complex space-time structure of the ocean current field in order to plan a path that optimizes scientific payoff and navigation efficiency. This letter demonstrates the capability of dynamical system theory for achieving this goal by realizing the real-time navigation strategy for the transoceanic AUV named Silbo, which is a Slocum deep-glider (0-1000 m), that crossed the North Atlantic from April 2016 to March 2017. Path planning in real time based on this approach has facilitated an impressive speed up of the AUV to unprecedented velocities resulting in major battery savings on the mission, offering the potential for routine transoceanic long duration missions.

Conflict-free trajectory planning for air traffic control automation

NASA Technical Reports Server (NTRS)

Slattery, Rhonda; Green, Steve

1994-01-01

As the traffic demand continues to grow within the National Airspace System (NAS), the need for long-range planning (30 minutes plus) of arrival traffic increases greatly. Research into air traffic control (ATC) automation at ARC has led to the development of the Center-TRACON Automation System (CTAS). CTAS determines optimum landing schedules for arrival traffic and assists controllers in meeting those schedules safely and efficiently. One crucial element in the development of CTAS is the capability to perform long-range (20 minutes) and short-range (5 minutes) conflict prediction and resolution once landing schedules are determined. The determination of conflict-free trajectories within the Center airspace is particularly difficult because of large variations in speed and altitude. The paper describes the current design and implementation of the conflict prediction and resolution tools used to generate CTAS advisories in Center airspace. Conflict criteria (separation requirements) are defined and the process of separation prediction is described. The major portion of the paper will describe the current implementation of CTAS conflict resolution algorithms in terms of the degrees of freedom for resolutions as well as resolution search techniques. The tools described in this paper have been implemented in a research system designed to rapidly develop and evaluate prototype concepts and will form the basis for an operational ATC automation system.

EPA Critical Path Science Plan Projects 19, 20 and 21: Human and Bovine Source Detection

EPA Science Inventory

The U.S. EPA Critical Path Science Plan Projects are: Project 19: develop novel bovine and human host-specific PCR assays and complete performance evaluation with other published methods. Project 20: Evaluate human-specific assays with water samples impacted with different lev...

A variational dynamic programming approach to robot-path planning with a distance-safety criterion

NASA Technical Reports Server (NTRS)

Suh, Suk-Hwan; Shin, Kang G.

1988-01-01

An approach to robot-path planning is developed by considering both the traveling distance and the safety of the robot. A computationally-efficient algorithm is developed to find a near-optimal path with a weighted distance-safety criterion by using a variational calculus and dynamic programming (VCDP) method. The algorithm is readily applicable to any factory environment by representing the free workspace as channels. A method for deriving these channels is also proposed. Although it is developed mainly for two-dimensional problems, this method can be easily extended to a class of three-dimensional problems. Numerical examples are presented to demonstrate the utility and power of this method.

UCAV path planning in the presence of radar-guided surface-to-air missile threats

NASA Astrophysics Data System (ADS)

Zeitz, Frederick H., III

This dissertation addresses the problem of path planning for unmanned combat aerial vehicles (UCAVs) in the presence of radar-guided surface-to-air missiles (SAMs). The radars, collocated with SAM launch sites, operate within the structure of an Integrated Air Defense System (IADS) that permits communication and cooperation between individual radars. The problem is formulated in the framework of the interaction between three sub-systems: the aircraft, the IADS, and the missile. The main features of this integrated model are: The aircraft radar cross section (RCS) depends explicitly on both the aspect and bank angles; hence, the RCS and aircraft dynamics are coupled. The probabilistic nature of IADS tracking is accounted for; namely, the probability that the aircraft has been continuously tracked by the IADS depends on the aircraft RCS and range from the perspective of each radar within the IADS. Finally, the requirement to maintain tracking prior to missile launch and during missile flyout are also modeled. Based on this model, the problem of UCAV path planning is formulated as a minimax optimal control problem, with the aircraft bank angle serving as control. Necessary conditions of optimality for this minimax problem are derived. Based on these necessary conditions, properties of the optimal paths are derived. These properties are used to discretize the dynamic optimization problem into a finite-dimensional, nonlinear programming problem that can be solved numerically. Properties of the optimal paths are also used to initialize the numerical procedure. A homotopy method is proposed to solve the finite-dimensional, nonlinear programming problem, and a heuristic method is proposed to improve the discretization during the homotopy process. Based upon the properties of numerical solutions, a method is proposed for parameterizing and storing information for later recall in flight to permit rapid replanning in response to changing threats. Illustrative examples are

Computational path planner for product assembly in complex environments

NASA Astrophysics Data System (ADS)

Shang, Wei; Liu, Jianhua; Ning, Ruxin; Liu, Mi

2013-03-01

Assembly path planning is a crucial problem in assembly related design and manufacturing processes. Sampling based motion planning algorithms are used for computational assembly path planning. However, the performance of such algorithms may degrade much in environments with complex product structure, narrow passages or other challenging scenarios. A computational path planner for automatic assembly path planning in complex 3D environments is presented. The global planning process is divided into three phases based on the environment and specific algorithms are proposed and utilized in each phase to solve the challenging issues. A novel ray test based stochastic collision detection method is proposed to evaluate the intersection between two polyhedral objects. This method avoids fake collisions in conventional methods and degrades the geometric constraint when a part has to be removed with surface contact with other parts. A refined history based rapidly-exploring random tree (RRT) algorithm which bias the growth of the tree based on its planning history is proposed and employed in the planning phase where the path is simple but the space is highly constrained. A novel adaptive RRT algorithm is developed for the path planning problem with challenging scenarios and uncertain environment. With extending values assigned on each tree node and extending schemes applied, the tree can adapts its growth to explore complex environments more efficiently. Experiments on the key algorithms are carried out and comparisons are made between the conventional path planning algorithms and the presented ones. The comparing results show that based on the proposed algorithms, the path planner can compute assembly path in challenging complex environments more efficiently and with higher success. This research provides the references to the study of computational assembly path planning under complex environments.

Kinematics, controls, and path planning results for a redundant manipulator

NASA Technical Reports Server (NTRS)

Gretz, Bruce; Tilley, Scott W.

1989-01-01

The inverse kinematics solution, a modal position control algorithm, and path planning results for a 7 degree of freedom manipulator are presented. The redundant arm consists of two links with shoulder and elbow joints and a spherical wrist. The inverse kinematics problem for tip position is solved and the redundant joint is identified. It is also shown that a locus of tip positions exists in which there are kinematic limitations on self-motion. A computationally simple modal position control algorithm has been developed which guarantees a nearly constant closed-loop dynamic response throughout the workspace. If all closed-loop poles are assigned to the same location, the algorithm can be implemented with very little computation. To further reduce the required computation, the modal gains are updated only at discrete time intervals. Criteria are developed for the frequency of these updates. For commanding manipulator movements, a 5th-order spline which minimizes jerk provides a smooth tip-space path. Schemes for deriving a corresponding joint-space trajectory are discussed. Modifying the trajectory to avoid joint torque saturation when a tip payload is added is also considered. Simulation results are presented.

Further Automate Planned Cluster Maintenance to Minimize System Downtime during Maintenance Windows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Springmeyer, R.

This report documents the integration and testing of the automated update process of compute clusters in LC to minimize impact to user productivity. Description: A set of scripts will be written and deployed to further standardize cluster maintenance activities and minimize downtime during planned maintenance windows. Completion Criteria: When the scripts have been deployed and used during planned maintenance windows and a timing comparison is completed between the existing process and the new more automated process, this milestone is complete. This milestone was completed on Aug 23, 2016 on the new CTS1 cluster called Jade when a request to upgrademore » the version of TOSS 3 was initiated while SWL jobs and normal user jobs were running. Jobs that were running when the update to the system began continued to run to completion. New jobs on the cluster started on the new release of TOSS 3. No system administrator action was required. Current update procedures in TOSS 2 begin by killing all users jobs. Then all diskfull nodes are updated, which can take a few hours. Only after the updates are applied are all nodes are rebooted, and then finally put back into service. A system administrator is required for all steps. In terms of human time spent during a cluster OS update, the TOSS 3 automated procedure on Jade took 0 FTE hours. Doing the same update without the Toss Update Tool would have required 4 FTE hours.« less

Methodology for Augmenting Existing Paths with Additional Parallel Transects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilson, John E.

2013-09-30

Visual Sample Plan (VSP) is sample planning software that is used, among other purposes, to plan transect sampling paths to detect areas that were potentially used for munition training. This module was developed for application on a large site where existing roads and trails were to be used as primary sampling paths. Gap areas between these primary paths needed to found and covered with parallel transect paths. These gap areas represent areas on the site that are more than a specified distance from a primary path. These added parallel paths needed to optionally be connected together into a single path—themore » shortest path possible. The paths also needed to optionally be attached to existing primary paths, again with the shortest possible path. Finally, the process must be repeatable and predictable so that the same inputs (primary paths, specified distance, and path options) will result in the same set of new paths every time. This methodology was developed to meet those specifications.« less

The Challenge of Grounding Planning in Simulation with an Interactive Model Development Environment

NASA Technical Reports Server (NTRS)

Clement, Bradley J.; Frank, Jeremy D.; Chachere, John M.; Smith, Tristan B.; Swanson, Keith J.

2011-01-01

A principal obstacle to fielding automated planning systems is the difficulty of modeling. Physical systems are modeled conventionally based on specification documents and the modeler's understanding of the system. Thus, the model is developed in a way that is disconnected from the system's actual behavior and is vulnerable to manual error. Another obstacle to fielding planners is testing and validation. For a space mission, generated plans must be validated often by translating them into command sequences that are run in a simulation testbed. Testing in this way is complex and onerous because of the large number of possible plans and states of the spacecraft. Though, if used as a source of domain knowledge, the simulator can ease validation. This paper poses a challenge: to ground planning models in the system physics represented by simulation. A proposed, interactive model development environment illustrates the integration of planning and simulation to meet the challenge. This integration reveals research paths for automated model construction and validation.

SciBox, an end-to-end automated science planning and commanding system

NASA Astrophysics Data System (ADS)

Choo, Teck H.; Murchie, Scott L.; Bedini, Peter D.; Steele, R. Josh; Skura, Joseph P.; Nguyen, Lillian; Nair, Hari; Lucks, Michael; Berman, Alice F.; McGovern, James A.; Turner, F. Scott

2014-01-01

SciBox is a new technology for planning and commanding science operations for Earth-orbital and planetary space missions. It has been incrementally developed since 2001 and demonstrated on several spaceflight projects. The technology has matured to the point that it is now being used to plan and command all orbital science operations for the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) mission to Mercury. SciBox encompasses the derivation of observing sequences from science objectives, the scheduling of those sequences, the generation of spacecraft and instrument commands, and the validation of those commands prior to uploading to the spacecraft. Although the process is automated, science and observing requirements are incorporated at each step by a series of rules and parameters to optimize observing opportunities, which are tested and validated through simulation and review. Except for limited special operations and tests, there is no manual scheduling of observations or construction of command sequences. SciBox reduces the lead time for operations planning by shortening the time-consuming coordination process, reduces cost by automating the labor-intensive processes of human-in-the-loop adjudication of observing priorities, reduces operations risk by systematically checking constraints, and maximizes science return by fully evaluating the trade space of observing opportunities to meet MESSENGER science priorities within spacecraft recorder, downlink, scheduling, and orbital-geometry constraints.

Radial polar histogram: obstacle avoidance and path planning for robotic cognition and motion control

NASA Astrophysics Data System (ADS)

Wang, Po-Jen; Keyawa, Nicholas R.; Euler, Craig

2012-01-01

In order to achieve highly accurate motion control and path planning for a mobile robot, an obstacle avoidance algorithm that provided a desired instantaneous turning radius and velocity was generated. This type of obstacle avoidance algorithm, which has been implemented in California State University Northridge's Intelligent Ground Vehicle (IGV), is known as Radial Polar Histogram (RPH). The RPH algorithm utilizes raw data in the form of a polar histogram that is read from a Laser Range Finder (LRF) and a camera. A desired open block is determined from the raw data utilizing a navigational heading and an elliptical approximation. The left and right most radii are determined from the calculated edges of the open block and provide the range of possible radial paths the IGV can travel through. In addition, the calculated obstacle edge positions allow the IGV to recognize complex obstacle arrangements and to slow down accordingly. A radial path optimization function calculates the best radial path between the left and right most radii and is sent to motion control for speed determination. Overall, the RPH algorithm allows the IGV to autonomously travel at average speeds of 3mph while avoiding all obstacles, with a processing time of approximately 10ms.

Systems planning for automated commercial vehicle licensing and permitting systems : national ITS/CVO program requirements

DOT National Transportation Integrated Search

1997-07-01

This report describes the work of the study, Systems Planning for Automated Commercial Vehicle Licensing and Permitting Systems. The objective of this study is to define the market, organization, and resource requirements for a national program...

Human Resources Planning for Office Automation.

ERIC Educational Resources Information Center

Munoz, Judith T.

1985-01-01

Examination of the transition to automated offices revealed that the prospect can be anxiety-producing for potential users, most users did not receive adequate training, lack of training may cause equipment underutilization, administrators are often not prepared to manage the change, and most experienced job satisfaction after automation. (MSE)

Feasible Path Generation Using Bezier Curves for Car-Like Vehicle

NASA Astrophysics Data System (ADS)

Latip, Nor Badariyah Abdul; Omar, Rosli

2017-08-01

When planning a collision-free path for an autonomous vehicle, the main criteria that have to be considered are the shortest distance, lower computation time and completeness, i.e. a path can be found if one exists. Besides that, a feasible path for the autonomous vehicle is also crucial to guarantee that the vehicle can reach the target destination considering its kinematic constraints such as non-holonomic and minimum turning radius. In order to address these constraints, Bezier curves is applied. In this paper, Bezier curves are modeled and simulated using Matlab software and the feasibility of the resulting path is analyzed. Bezier curve is derived from a piece-wise linear pre-planned path. It is found that the Bezier curves has the capability of making the planned path feasible and could be embedded in a path planning algorithm for an autonomous vehicle with kinematic constraints. It is concluded that the length of segments of the pre-planned path have to be greater than a nominal value, derived from the vehicle wheelbase, maximum steering angle and maximum speed to ensure the path for the autonomous car is feasible.

Logistics Automation Master Plan (LAMP). Better Logistics Support through Automation.

DTIC Science & Technology

1983-06-01

office micro-computers, positioned throughout the command chain , by providing real time links between LCA and all users: 2. Goals: Assist HQDA staff in...field i.e., Airland Battle 2000. IV-27 Section V: CONCEPT OF EXECUTION Suply (Retail) A. SRstem Description. I. The Division Logistics Property Book...7. Divisional Direct Support Unit Automated Supply System (DDASS)/Direct pport Level Suply Automation (DLSA). DDASS and DLSA are system development

FMEA of manual and automated methods for commissioning a radiotherapy treatment planning system.

PubMed

Wexler, Amy; Gu, Bruce; Goddu, Sreekrishna; Mutic, Maya; Yaddanapudi, Sridhar; Olsen, Lindsey; Harry, Taylor; Noel, Camille; Pawlicki, Todd; Mutic, Sasa; Cai, Bin

2017-09-01

To evaluate the level of risk involved in treatment planning system (TPS) commissioning using a manual test procedure, and to compare the associated process-based risk to that of an automated commissioning process (ACP) by performing an in-depth failure modes and effects analysis (FMEA). The authors collaborated to determine the potential failure modes of the TPS commissioning process using (a) approaches involving manual data measurement, modeling, and validation tests and (b) an automated process utilizing application programming interface (API) scripting, preloaded, and premodeled standard radiation beam data, digital heterogeneous phantom, and an automated commissioning test suite (ACTS). The severity (S), occurrence (O), and detectability (D) were scored for each failure mode and the risk priority numbers (RPN) were derived based on TG-100 scale. Failure modes were then analyzed and ranked based on RPN. The total number of failure modes, RPN scores and the top 10 failure modes with highest risk were described and cross-compared between the two approaches. RPN reduction analysis is also presented and used as another quantifiable metric to evaluate the proposed approach. The FMEA of a MTP resulted in 47 failure modes with an RPN ave of 161 and S ave of 6.7. The highest risk process of "Measurement Equipment Selection" resulted in an RPN max of 640. The FMEA of an ACP resulted in 36 failure modes with an RPN ave of 73 and S ave of 6.7. The highest risk process of "EPID Calibration" resulted in an RPN max of 576. An FMEA of treatment planning commissioning tests using automation and standardization via API scripting, preloaded, and pre-modeled standard beam data, and digital phantoms suggests that errors and risks may be reduced through the use of an ACP. © 2017 American Association of Physicists in Medicine.

A 2D chaotic path planning for mobile robots accomplishing boundary surveillance missions in adversarial conditions

NASA Astrophysics Data System (ADS)

Curiac, Daniel-Ioan; Volosencu, Constantin

2014-10-01

The path-planning algorithm represents a crucial issue for every autonomous mobile robot. In normal circumstances a patrol robot will compute an optimal path to ensure its task accomplishment, but in adversarial conditions the problem is getting more complicated. Here, the robot’s trajectory needs to be altered into a misleading and unpredictable path to cope with potential opponents. Chaotic systems provide the needed framework for obtaining unpredictable motion in all of the three basic robot surveillance missions: area, points of interests and boundary monitoring. Proficient approaches have been provided for the first two surveillance tasks, but for boundary patrol missions no method has been reported yet. This paper addresses the mentioned research gap by proposing an efficient method, based on chaotic dynamic of the Hénon system, to ensure unpredictable boundary patrol on any shape of chosen closed contour.

An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning.

PubMed

Li, Bai; Gong, Li-gang; Yang, Wen-lun

2014-01-01

Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.

Path planning for assembly of strut-based structures. Thesis

NASA Technical Reports Server (NTRS)

Muenger, Rolf

1991-01-01

A path planning method with collision avoidance for a general single chain nonredundant or redundant robot is proposed. Joint range boundary overruns are also avoided. The result is a sequence of joint vectors which are passed to a trajectory planner. A potential field algorithm in joint space computes incremental joint vectors delta-q = delta-q(sub a) + delta-q(sub c) + delta-q(sub r). Adding delta-q to the robot's current joint vector leads to the next step in the path. Delta-q(sub a) is obtained by computing the minimum norm solution of the underdetermined linear system J delta-q(sub a) = x(sub a) where x(sub a) is a translational and rotational force vector that attracts the robot to its goal position and orientation. J is the manipulator Jacobian. Delta-q(sub c) is a collision avoidance term encompassing collisions between the robot (links and payload) and obstacles in the environment as well as collisions among links and payload of the robot themselves. It is obtained in joint space directly. Delta-q(sub r) is a function of the current joint vector and avoids joint range overruns. A higher level discrete search over candidate safe positions is used to provide alternatives in case the potential field algorithm encounters a local minimum and thus fails to reach the goal. The best first search algorithm A* is used for graph search. Symmetry properties of the payload and equivalent rotations are exploited to further enlarge the number of alternatives passed to the potential field algorithm.

Automation of Coordinated Planning Between Observatories: The Visual Observation Layout Tool (VOLT)

NASA Technical Reports Server (NTRS)

Maks, Lori; Koratkar, Anuradha; Kerbel, Uri; Pell, Vince

2002-01-01

Fulfilling the promise of the era of great observatories, NASA now has more than three space-based astronomical telescopes operating in different wavebands. This situation provides astronomers with the unique opportunity of simultaneously observing a target in multiple wavebands with these observatories. Currently scheduling multiple observatories simultaneously, for coordinated observations, is highly inefficient. Coordinated observations require painstaking manual collaboration among the observatory staff at each observatory. Because they are time-consuming and expensive to schedule, observatories often limit the number of coordinated observations that can be conducted. In order to exploit new paradigms for observatory operation, the Advanced Architectures and Automation Branch of NASA's Goddard Space Flight Center has developed a tool called the Visual Observation Layout Tool (VOLT). The main objective of VOLT is to provide a visual tool to automate the planning of coordinated observations by multiple astronomical observatories. Four of NASA's space-based astronomical observatories - the Hubble Space Telescope (HST), Far Ultraviolet Spectroscopic Explorer (FUSE), Rossi X-ray Timing Explorer (RXTE) and Chandra - are enthusiastically pursuing the use of VOLT. This paper will focus on the purpose for developing VOLT, as well as the lessons learned during the infusion of VOLT into the planning and scheduling operations of these observatories.

Automated and connected vehicle (AV/CV) test bed to improve transit, bicycle, and pedestrian safety : concept of operations plan.

DOT National Transportation Integrated Search

2017-02-01

This document presents the Concept of Operations (ConOps) Plan for the Automated and Connected Vehicle (AV/CV) Test Bed to Improve Transit, Bicycle, and Pedestrian Safety. As illustrated in Figure 1, the plan presents the overarching vision and goals...

Automated and Adaptive Mission Planning for Orbital Express

NASA Technical Reports Server (NTRS)

Chouinard, Caroline; Knight, Russell; Jones, Grailing; Tran, Daniel; Koblick, Darin

2008-01-01

The Orbital Express space mission was a Defense Advanced Research Projects Agency (DARPA) lead demonstration of on-orbit satellite servicing scenarios, autonomous rendezvous, fluid transfers of hydrazine propellant, and robotic arm transfers of Orbital Replacement Unit (ORU) components. Boeing's Autonomous Space Transport Robotic Operations (ASTRO) vehicle provided the servicing to the Ball Aerospace's Next Generation Serviceable Satellite (NextSat) client. For communication opportunities, operations used the high-bandwidth ground-based Air Force Satellite Control Network (AFSCN) along with the relatively low-bandwidth GEO-Synchronous space-borne Tracking and Data Relay Satellite System (TDRSS) network. Mission operations were conducted out of the RDT&E Support Complex (RSC) at the Kirtland Air Force Base in New Mexico. All mission objectives were met successfully: The first of several autonomous rendezvous was demonstrated on May 5, 2007; autonomous free-flyer capture was demonstrated on June 22, 2007; the fluid and ORU transfers throughout the mission were successful. Planning operations for the mission were conducted by a team of personnel including Flight Directors, who were responsible for verifying the steps and contacts within the procedures, the Rendezvous Planners who would compute the locations and visibilities of the spacecraft, the Scenario Resource Planners (SRPs), who were concerned with assignment of communications windows, monitoring of resources, and sending commands to the ASTRO spacecraft, and the Mission planners who would interface with the real-time operations environment, process planning products and coordinate activities with the SRP. The SRP position was staffed by JPL personnel who used the Automated Scheduling and Planning ENvironment (ASPEN) to model and enforce mission and satellite constraints. The lifecycle of a plan began three weeks outside its execution on-board. During the planning timeframe, many aspects could change the plan

PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results.

PubMed

He, Ji; Dai, Xinbin; Zhao, Xuechun

2007-02-09

BLAST searches are widely used for sequence alignment. The search results are commonly adopted for various functional and comparative genomics tasks such as annotating unknown sequences, investigating gene models and comparing two sequence sets. Advances in sequencing technologies pose challenges for high-throughput analysis of large-scale sequence data. A number of programs and hardware solutions exist for efficient BLAST searching, but there is a lack of generic software solutions for mining and personalized management of the results. Systematically reviewing the results and identifying information of interest remains tedious and time-consuming. Personal BLAST Navigator (PLAN) is a versatile web platform that helps users to carry out various personalized pre- and post-BLAST tasks, including: (1) query and target sequence database management, (2) automated high-throughput BLAST searching, (3) indexing and searching of results, (4) filtering results online, (5) managing results of personal interest in favorite categories, (6) automated sequence annotation (such as NCBI NR and ontology-based annotation). PLAN integrates, by default, the Decypher hardware-based BLAST solution provided by Active Motif Inc. with a greatly improved efficiency over conventional BLAST software. BLAST results are visualized by spreadsheets and graphs and are full-text searchable. BLAST results and sequence annotations can be exported, in part or in full, in various formats including Microsoft Excel and FASTA. Sequences and BLAST results are organized in projects, the data publication levels of which are controlled by the registered project owners. In addition, all analytical functions are provided to public users without registration. PLAN has proved a valuable addition to the community for automated high-throughput BLAST searches, and, more importantly, for knowledge discovery, management and sharing based on sequence alignment results. The PLAN web interface is platform

The use of 3-D sensing techniques for on-line collision-free path planning

NASA Technical Reports Server (NTRS)

Hayward, V.; Aubry, S.; Jasiukajc, Z.

1987-01-01

The state of the art in collision prevention for manipulators with revolute joints, showing that it is a particularly computationally hard problem, is discussed. Based on the analogy with other hard or undecidable problems such as theorem proving, an extensible multi-resolution architecture for path planning, based on a collection of weak methods is proposed. Finally, the role that sensors can play for an on-line use of sensor data is examined.

Improved plan quality with automated radiotherapy planning for whole brain with hippocampus sparing: a comparison to the RTOG 0933 trial.

PubMed

Krayenbuehl, J; Di Martino, M; Guckenberger, M; Andratschke, N

2017-10-02

Whole-brain radiation therapy (WBRT) with hippocampus sparing (HS) has been investigated by the radiation oncology working group (RTOG) 0933 trial for patients with multiple brain metastases. They showed a decrease of adverse neurocognitive effects with HS WBRT compared to WBRT alone. With the development of automated treatment planning system (aTPS) in the last years, a standardization of the plan quality at a high level was achieved. The goal of this study was to evaluate the feasibility of using an aTPS for the treatment of HS WBRT and see if the RTOG 0933 dose constraints could be achieved and improved. Ten consecutive patients treated with HS WBRT were enrolled in this study. 10 × 3 Gy was prescribed according to the RTOG 0933 protocol to 92% of the target volume (whole-brain excluding the hippocampus expanded by 5 mm in 3-dimensions). In contrast to RTOG 0933, the maximum allowed point dose to normal brain was significantly lowered and restricted to 36.5 Gy. All patients were planned with volumetric modulated arc therapy (VMAT) technique using four arcs. Plans were optimized using Auto-Planning (AP) (Philips Radiation Oncology Systems) with one single AP template and optimization. All the constraints from the RTOG 0933 trial were achieved. A significant improvement for the maximal dose to 2% of the brain with a reduction of 4 Gy was achieved (33.5 Gy vs. RTOG 37.5 Gy) and the minimum hippocampus dose was reduced by 10% (8.1 Gy vs. RTOG 9 Gy). A steep dose gradient around the hippocampus was achieved with a mean dose of 27.3 Gy at a distance between 0.5 cm and 1 cm from the hippocampus. The effective working time to optimize a plan was kept below 6'. Automated treatment planning for HS WBRT was able to fulfil all the recommendations from the RTOG 0933 study while significantly improving dose homogeneity and decreasing unnecessary hot spot in the normal brain. With this approach, a standardization of plan quality was achieved and the effective

Predictive Sea State Estimation for Automated Ride Control and Handling - PSSEARCH

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance L.; Howard, Andrew B.; Aghazarian, Hrand; Rankin, Arturo L.

2012-01-01

PSSEARCH provides predictive sea state estimation, coupled with closed-loop feedback control for automated ride control. It enables a manned or unmanned watercraft to determine the 3D map and sea state conditions in its vicinity in real time. Adaptive path-planning/ replanning software and a control surface management system will then use this information to choose the best settings and heading relative to the seas for the watercraft. PSSEARCH looks ahead and anticipates potential impact of waves on the boat and is used in a tight control loop to adjust trim tabs, course, and throttle settings. The software uses sensory inputs including IMU (Inertial Measurement Unit), stereo, radar, etc. to determine the sea state and wave conditions (wave height, frequency, wave direction) in the vicinity of a rapidly moving boat. This information can then be used to plot a safe path through the oncoming waves. The main issues in determining a safe path for sea surface navigation are: (1) deriving a 3D map of the surrounding environment, (2) extracting hazards and sea state surface state from the imaging sensors/map, and (3) planning a path and control surface settings that avoid the hazards, accomplish the mission navigation goals, and mitigate crew injuries from excessive heave, pitch, and roll accelerations while taking into account the dynamics of the sea surface state. The first part is solved using a wide baseline stereo system, where 3D structure is determined from two calibrated pairs of visual imagers. Once the 3D map is derived, anything above the sea surface is classified as a potential hazard and a surface analysis gives a static snapshot of the waves. Dynamics of the wave features are obtained from a frequency analysis of motion vectors derived from the orientation of the waves during a sequence of inputs. Fusion of the dynamic wave patterns with the 3D maps and the IMU outputs is used for efficient safe path planning.

Motion Planning for Autonomous Vehicle Based on Radial Basis Function Neural Network in Unstructured Environment

PubMed Central

Chen, Jiajia; Zhao, Pan; Liang, Huawei; Mei, Tao

2014-01-01

The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality. PMID:25237902

Motion planning for autonomous vehicle based on radial basis function neural network in unstructured environment.

PubMed

Chen, Jiajia; Zhao, Pan; Liang, Huawei; Mei, Tao

2014-09-18

The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality.

Automated Data Processing as an AI Planning Problem

NASA Technical Reports Server (NTRS)

Golden, Keith; Pang, Wanlin; Nemani, Ramakrishna; Votava, Petr

2003-01-01

NASA s vision for Earth Science is to build a "sensor web"; an adaptive array of heterogeneous satellites and other sensors that will track important events, such as storms, and provide real-time information about the state of the Earth to a wide variety of customers. Achieving his vision will require automation not only in the scheduling of the observations but also in the processing af tee resulting data. Ta address this need, we have developed a planner-based agent to automatically generate and execute data-flow programs to produce the requested data products. Data processing domains are substantially different from other planning domains that have been explored, and this has led us to substantially different choices in terms of representation and algorithms. We discuss some of these differences and discuss the approach we have adopted.

Automation of Oklahoma School Library Media Centers: Automation at the Local Level.

ERIC Educational Resources Information Center

Oklahoma State Dept. of Education, Oklahoma City. Library and Learning Resources Section.

This document outlines a workshop for media specialists--"School Library Automation: Solving the Puzzle"--that is designed to reduce automation anxiety and give a broad overview of the concerns confronting school library media centers planning for or involved in automation. Issues are addressed under the following headings: (1) Levels of School…

Enroute flight-path planning - Cooperative performance of flight crews and knowledge-based systems

NASA Technical Reports Server (NTRS)

Smith, Philip J.; Mccoy, Elaine; Layton, Chuck; Galdes, Deb

1989-01-01

Interface design issues associated with the introduction of knowledge-based systems into the cockpit are discussed. Such issues include not only questions about display and control design, they also include deeper system design issues such as questions about the alternative roles and responsibilities of the flight crew and the computer system. In addition, the feasibility of using enroute flight path planning as a context for exploring such research questions is considered. In particular, the development of a prototyping shell that allows rapid design and study of alternative interfaces and system designs is discussed.

Energy-optimal path planning in the coastal ocean

NASA Astrophysics Data System (ADS)

Subramani, Deepak N.; Haley, Patrick J.; Lermusiaux, Pierre F. J.

2017-05-01

We integrate data-driven ocean modeling with the stochastic Dynamically Orthogonal (DO) level-set optimization methodology to compute and study energy-optimal paths, speeds, and headings for ocean vehicles in the Middle-Atlantic Bight (MAB) region. We hindcast the energy-optimal paths from among exact time-optimal paths for the period 28 August 2006 to 9 September 2006. To do so, we first obtain a data-assimilative multiscale reanalysis, combining ocean observations with implicit two-way nested multiresolution primitive-equation simulations of the tidal-to-mesoscale dynamics in the region. Second, we solve the reduced-order stochastic DO level-set partial differential equations (PDEs) to compute the joint probability of minimum arrival time, vehicle-speed time series, and total energy utilized. Third, for each arrival time, we select the vehicle-speed time series that minimize the total energy utilization from the marginal probability of vehicle-speed and total energy. The corresponding energy-optimal path and headings are obtained through the exact particle-backtracking equation. Theoretically, the present methodology is PDE-based and provides fundamental energy-optimal predictions without heuristics. Computationally, it is 3-4 orders of magnitude faster than direct Monte Carlo methods. For the missions considered, we analyze the effects of the regional tidal currents, strong wind events, coastal jets, shelfbreak front, and other local circulations on the energy-optimal paths. Results showcase the opportunities for vehicles that intelligently utilize the ocean environment to minimize energy usage, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

Automated Procurement System (APS): Project management plan (DS-03), version 1.2

NASA Technical Reports Server (NTRS)

Murphy, Diane R.

1994-01-01

The National Aeronautics and Space Administration (NASA) Marshall Space Flight Center (MSFC) is implementing an Automated Procurement System (APS) to streamline its business activities that are used to procure goods and services. This Project Management Plan (PMP) is the governing document throughout the implementation process and is identified as the APS Project Management Plan (DS-03). At this point in time, the project plan includes the schedules and tasks necessary to proceed through implementation. Since the basis of APS is an existing COTS system, the implementation process is revised from the standard SDLC. The purpose of the PMP is to provide the framework for the implementation process. It discusses the roles and responsibilities of the NASA project staff, the functions to be performed by the APS Development Contractor (PAI), and the support required of the NASA computer support contractor (CSC). To be successful, these three organizations must work together as a team, working towards the goals established in this Project Plan. The Project Plan includes a description of the proposed system, describes the work to be done, establishes a schedule of deliverables, and discusses the major standards and procedures to be followed.

Automation of radiation treatment planning : Evaluation of head and neck cancer patient plans created by the Pinnacle3 scripting and Auto-Planning functions.

PubMed

Speer, Stefan; Klein, Andreas; Kober, Lukas; Weiss, Alexander; Yohannes, Indra; Bert, Christoph

2017-08-01

Intensity-modulated radiotherapy (IMRT) techniques are now standard practice. IMRT or volumetric-modulated arc therapy (VMAT) allow treatment of the tumor while simultaneously sparing organs at risk. Nevertheless, treatment plan quality still depends on the physicist's individual skills, experiences, and personal preferences. It would therefore be advantageous to automate the planning process. This possibility is offered by the Pinnacle 3 treatment planning system (Philips Healthcare, Hamburg, Germany) via its scripting language or Auto-Planning (AP) module. AP module results were compared to in-house scripts and manually optimized treatment plans for standard head and neck cancer plans. Multiple treatment parameters were scored to judge plan quality (100 points = optimum plan). Patients were initially planned manually by different physicists and re-planned using scripts or AP. Script-based head and neck plans achieved a mean of 67.0 points and were, on average, superior to manually created (59.1 points) and AP plans (62.3 points). Moreover, they are characterized by reproducibility and lower standard deviation of treatment parameters. Even less experienced staff are able to create at least a good starting point for further optimization in a short time. However, for particular plans, experienced planners perform even better than scripts or AP. Experienced-user input is needed when setting up scripts or AP templates for the first time. Moreover, some minor drawbacks exist, such as the increase of monitor units (+35.5% for scripted plans). On average, automatically created plans are superior to manually created treatment plans. For particular plans, experienced physicists were able to perform better than scripts or AP; thus, the benefit is greatest when time is short or staff inexperienced.

PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results

PubMed Central

He, Ji; Dai, Xinbin; Zhao, Xuechun

2007-01-01

Background BLAST searches are widely used for sequence alignment. The search results are commonly adopted for various functional and comparative genomics tasks such as annotating unknown sequences, investigating gene models and comparing two sequence sets. Advances in sequencing technologies pose challenges for high-throughput analysis of large-scale sequence data. A number of programs and hardware solutions exist for efficient BLAST searching, but there is a lack of generic software solutions for mining and personalized management of the results. Systematically reviewing the results and identifying information of interest remains tedious and time-consuming. Results Personal BLAST Navigator (PLAN) is a versatile web platform that helps users to carry out various personalized pre- and post-BLAST tasks, including: (1) query and target sequence database management, (2) automated high-throughput BLAST searching, (3) indexing and searching of results, (4) filtering results online, (5) managing results of personal interest in favorite categories, (6) automated sequence annotation (such as NCBI NR and ontology-based annotation). PLAN integrates, by default, the Decypher hardware-based BLAST solution provided by Active Motif Inc. with a greatly improved efficiency over conventional BLAST software. BLAST results are visualized by spreadsheets and graphs and are full-text searchable. BLAST results and sequence annotations can be exported, in part or in full, in various formats including Microsoft Excel and FASTA. Sequences and BLAST results are organized in projects, the data publication levels of which are controlled by the registered project owners. In addition, all analytical functions are provided to public users without registration. Conclusion PLAN has proved a valuable addition to the community for automated high-throughput BLAST searches, and, more importantly, for knowledge discovery, management and sharing based on sequence alignment results. The PLAN web interface

A taxonomy of integral reaction path analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grcar, Joseph F.; Day, Marcus S.; Bell, John B.

2004-12-23

W. C. Gardiner observed that achieving understanding through combustion modeling is limited by the ability to recognize the implications of what has been computed and to draw conclusions about the elementary steps underlying the reaction mechanism. This difficulty can be overcome in part by making better use of reaction path analysis in the context of multidimensional flame simulations. Following a survey of current practice, an integral reaction flux is formulated in terms of conserved scalars that can be calculated in a fully automated way. Conditional analyses are then introduced, and a taxonomy for bidirectional path analysis is explored. Many examplesmore » illustrate the resulting path analysis and uncover some new results about nonpremixed methane-air laminar jets.« less

SU-F-T-440: The Feasibility Research of Checking Cervical Cancer IMRT Pre- Treatment Dose Verification by Automated Treatment Planning Verification System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, X; Yin, Y; Lin, X

Purpose: To assess the preliminary feasibility of automated treatment planning verification system in cervical cancer IMRT pre-treatment dose verification. Methods: The study selected randomly clinical IMRT treatment planning data for twenty patients with cervical cancer, all IMRT plans were divided into 7 fields to meet the dosimetric goals using a commercial treatment planning system(PianncleVersion 9.2and the EclipseVersion 13.5). The plans were exported to the Mobius 3D (M3D)server percentage differences of volume of a region of interest (ROI) and dose calculation of target region and organ at risk were evaluated, in order to validate the accuracy automated treatment planning verification system.more » Results: The difference of volume for Pinnacle to M3D was less than results for Eclipse to M3D in ROI, the biggest difference was 0.22± 0.69%, 3.5±1.89% for Pinnacle and Eclipse respectively. M3D showed slightly better agreement in dose of target and organ at risk compared with TPS. But after recalculating plans by M3D, dose difference for Pinnacle was less than Eclipse on average, results were within 3%. Conclusion: The method of utilizing the automated treatment planning system to validate the accuracy of plans is convenientbut the scope of differences still need more clinical patient cases to determine. At present, it should be used as a secondary check tool to improve safety in the clinical treatment planning.« less

Comparison of VMAT and IMRT strategies for cervical cancer patients using automated planning.

PubMed

Sharfo, Abdul Wahab M; Voet, Peter W J; Breedveld, Sebastiaan; Mens, Jan Willem M; Hoogeman, Mischa S; Heijmen, Ben J M

2015-03-01

In a published study on cervical cancer, 5-beam IMRT was inferior to single arc VMAT. Here we compare 9, 12, and 20 beam IMRT with single and dual arc VMAT. For each of 10 patients, automated plan generation with the in-house Erasmus-iCycle optimizer was used to assist an expert planner in generating the five plans with the clinical TPS. For each patient, all plans were clinically acceptable with a high and similar PTV coverage. OAR sparing increased when going from 9 to 12 to 20 IMRT beams, and from single to dual arc VMAT. For all patients, 12 and 20 beam IMRT were superior to single and dual arc VMAT, with substantial variations in gain among the study patients. As expected, delivery of VMAT plans was significantly faster than delivery of IMRT plans. Often reported increased plan quality for VMAT compared to IMRT has not been observed for cervical cancer. Twenty and 12 beam IMRT plans had a higher quality than single and dual arc VMAT. For individual patients, the optimal delivery technique depends on a complex trade-off between plan quality and treatment time that may change with introduction of faster delivery systems. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Strategic Transit Automation Research Plan

DOT National Transportation Integrated Search

2018-01-01

Transit bus automation could deliver many potential benefits, but transit agencies need additional research and policy guidance to make informed deployment decisions. Although funding and policy constraints may play a role, there is also a reasonable...

Defining Advancement Career Paths and Succession Plans: Critical Human Capital Retention Strategies for High-Performing Advancement Divisions

ERIC Educational Resources Information Center

Croteau, Jon Derek; Wolk, Holly Gordon

2010-01-01

There are many factors that can influence whether a highly talented staff member will build a career within an institution or use it as a stepping stone. This article defines and explores the notions of developing career paths and succession planning and why they are critical human capital investment strategies in retaining the highest performers…

Optimal path planning for video-guided smart munitions via multitarget tracking

NASA Astrophysics Data System (ADS)

Borkowski, Jeffrey M.; Vasquez, Juan R.

2006-05-01

An advent in the development of smart munitions entails autonomously modifying target selection during flight in order to maximize the value of the target being destroyed. A unique guidance law can be constructed that exploits both attribute and kinematic data obtained from an onboard video sensor. An optimal path planning algorithm has been developed with the goals of obstacle avoidance and maximizing the value of the target impacted by the munition. Target identification and classification provides a basis for target value which is used in conjunction with multi-target tracks to determine an optimal waypoint for the munition. A dynamically feasible trajectory is computed to provide constraints on the waypoint selection. Results demonstrate the ability of the autonomous system to avoid moving obstacles and revise target selection in flight.

Digital Parallel Processor Array for Optimum Path Planning

NASA Technical Reports Server (NTRS)

Kremeny, Sabrina E. (Inventor); Fossum, Eric R. (Inventor); Nixon, Robert H. (Inventor)

1996-01-01

The invention computes the optimum path across a terrain or topology represented by an array of parallel processor cells interconnected between neighboring cells by links extending along different directions to the neighboring cells. Such an array is preferably implemented as a high-speed integrated circuit. The computation of the optimum path is accomplished by, in each cell, receiving stimulus signals from neighboring cells along corresponding directions, determining and storing the identity of a direction along which the first stimulus signal is received, broadcasting a subsequent stimulus signal to the neighboring cells after a predetermined delay time, whereby stimulus signals propagate throughout the array from a starting one of the cells. After propagation of the stimulus signal throughout the array, a master processor traces back from a selected destination cell to the starting cell along an optimum path of the cells in accordance with the identity of the directions stored in each of the cells.

Planning and implementing total laboratory automation at the North Shore-Long Island Jewish Health System Laboratories.

PubMed

Seaberg, R C; Statland, B E; Stallone, R O

1999-06-01

Lab automation and consolidation can be a daunting, risky, major reengineering project. Done right, it can mean decreased labor costs and space requirements, increased test volume, and more efficient use of personnel. See how this health system got the job done using a carefully defined, seven-step plan.

Integrating obstacle avoidance, global path planning, visual cue detection, and landmark triangulation in a mobile robot

NASA Astrophysics Data System (ADS)

Kortenkamp, David; Huber, Marcus J.; Congdon, Clare B.; Huffman, Scott B.; Bidlack, Clint R.; Cohen, Charles J.; Koss, Frank V.; Raschke, Ulrich; Weymouth, Terry E.

1993-05-01

This paper describes the design and implementation of an integrated system for combining obstacle avoidance, path planning, landmark detection and position triangulation. Such an integrated system allows the robot to move from place to place in an environment, avoiding obstacles and planning its way out of traps, while maintaining its position and orientation using distinctive landmarks. The task the robot performs is to search a 22 m X 22 m arena for 10 distinctive objects, visiting each object in turn. This same task was recently performed by a dozen different robots at a competition in which the robot described in this paper finished first.

Path planning and parameter optimization of uniform removal in active feed polishing

NASA Astrophysics Data System (ADS)

Liu, Jian; Wang, Shaozhi; Zhang, Chunlei; Zhang, Linghua; Chen, Huanan

2015-06-01

A high-quality ultrasmooth surface is demanded in short-wave optical systems. However, the existing polishing methods have difficulties meeting the requirement on spherical or aspheric surfaces. As a new kind of small tool polishing method, active feed polishing (AFP) could attain a surface roughness of less than 0.3 nm (RMS) on spherical elements, although AFP may magnify the residual figure error or mid-frequency error. The purpose of this work is to propose an effective algorithm to realize uniform removal of the surface in the processing. At first, the principle of the AFP and the mechanism of the polishing machine are introduced. In order to maintain the processed figure error, a variable pitch spiral path planning algorithm and the dwell time-solving model are proposed. For suppressing the possible mid-frequency error, the uniformity of the synthesis tool path, which is generated by an arbitrary point at the polishing tool bottom, is analyzed and evaluated, and the angular velocity ratio of the tool spinning motion to the revolution motion is optimized. Finally, an experiment is conducted on a convex spherical surface and an ultrasmooth surface is finally acquired. In conclusion, a high-quality ultrasmooth surface can be successfully obtained with little degradation of the figure and mid-frequency errors by the algorithm.

Using AI/expert system technology to automate planning and replanning for the HST servicing missions

NASA Technical Reports Server (NTRS)

Bogovich, L.; Johnson, J; Tuchman, A.; Mclean, D.; Page, B.; Kispert, A.; Burkhardt, C.; Littlefield, R.; Potter, W.

1993-01-01

This paper describes a knowledge-based system that has been developed to automate planning and scheduling for the Hubble Space Telescope (HST) Servicing Missions. This new system is the Servicing Mission Planning and Replanning Tool (SM/PART). SM/PART has been delivered to the HST Flight Operations Team (FOT) at Goddard Space Flight Center (GSFC) where it is being used to build integrated time lines and command plans to control the activities of the HST, Shuttle, Crew and ground systems for the next HST Servicing Mission. SM/PART reuses and extends AI/expert system technology from Interactive Experimenter Planning System (IEPS) systems to build or rebuild time lines and command plans more rapidly than was possible for previous missions where they were built manually. This capability provides an important safety factor for the HST, Shuttle and Crew in case unexpected events occur during the mission.

Long Range Navigation for Mars Rovers Using Sensor-Based Path Planning and Visual Localisation

NASA Technical Reports Server (NTRS)

Laubach, Sharon L.; Olson, Clark F.; Burdick, Joel W.; Hayati, Samad

1999-01-01

The Mars Pathfinder mission illustrated the benefits of including a mobile robotic explorer on a planetary mission. However, for future Mars rover missions, significantly increased autonomy in navigation is required in order to meet demanding mission criteria. To address these requirements, we have developed new path planning and localisation capabilities that allow a rover to navigate robustly to a distant landmark. These algorithms have been implemented on the JPL Rocky 7 prototype microrover and have been tested extensively in the JPL MarsYard, as well as in natural terrain.

Voxel-based dose prediction with multi-patient atlas selection for automated radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

McIntosh, Chris; Purdie, Thomas G.

2017-01-01

Automating the radiotherapy treatment planning process is a technically challenging problem. The majority of automated approaches have focused on customizing and inferring dose volume objectives to be used in plan optimization. In this work we outline a multi-patient atlas-based dose prediction approach that learns to predict the dose-per-voxel for a novel patient directly from the computed tomography planning scan without the requirement of specifying any objectives. Our method learns to automatically select the most effective atlases for a novel patient, and then map the dose from those atlases onto the novel patient. We extend our previous work to include a conditional random field for the optimization of a joint distribution prior that matches the complementary goals of an accurately spatially distributed dose distribution while still adhering to the desired dose volume histograms. The resulting distribution can then be used for inverse-planning with a new spatial dose objective, or to create typical dose volume objectives for the canonical optimization pipeline. We investigated six treatment sites (633 patients for training and 113 patients for testing) and evaluated the mean absolute difference in all DVHs for the clinical and predicted dose distribution. The results on average are favorable in comparison to our previous approach (1.91 versus 2.57). Comparing our method with and without atlas-selection further validates that atlas-selection improved dose prediction on average in whole breast (0.64 versus 1.59), prostate (2.13 versus 4.07), and rectum (1.46 versus 3.29) while it is less important in breast cavity (0.79 versus 0.92) and lung (1.33 versus 1.27) for which there is high conformity and minimal dose shaping. In CNS brain, atlas-selection has the potential to be impactful (3.65 versus 5.09), but selecting the ideal atlas is the most challenging.

Research on Taxiway Path Optimization Based on Conflict Detection

PubMed Central

Zhou, Hang; Jiang, Xinxin

2015-01-01

Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency. PMID:26226485

Research on Taxiway Path Optimization Based on Conflict Detection.

PubMed

Zhou, Hang; Jiang, Xinxin

2015-01-01

Taxiway path planning is one of the effective measures to make full use of the airport resources, and the optimized paths can ensure the safety of the aircraft during the sliding process. In this paper, the taxiway path planning based on conflict detection is considered. Specific steps are shown as follows: firstly, make an improvement on A * algorithm, the conflict detection strategy is added to search for the shortest and safe path in the static taxiway network. Then, according to the sliding speed of aircraft, a time table for each node is determined and the safety interval is treated as the constraint to judge whether there is a conflict or not. The intelligent initial path planning model is established based on the results. Finally, make an example in an airport simulation environment, detect and relieve the conflict to ensure the safety. The results indicate that the model established in this paper is effective and feasible. Meanwhile, make comparison with the improved A*algorithm and other intelligent algorithms, conclude that the improved A*algorithm has great advantages. It could not only optimize taxiway path, but also ensure the safety of the sliding process and improve the operational efficiency.

Planning Minimum-Energy Paths in an Off-Road Environment with Anisotropic Traversal Costs and Motion Constraints

DTIC Science & Technology

1989-06-01

problems, and (3) weighted-region problems. Since the minimum-energy path-planning problem addressed in this dissertation is a hybrid between the two...contains components that are strictly vehicle dependent, components that are strictly terrain dependent, and components representing a hybrid of...Single Segment Braking/Multiple Segment Hybrid Using Eq. (3.46), the traversal cost U 1,.-1 can be rewritten as Uop- 1 = mgD Itan01 , (4.12a) and the

Rectangular Array Of Digital Processors For Planning Paths

NASA Technical Reports Server (NTRS)

Kemeny, Sabrina E.; Fossum, Eric R.; Nixon, Robert H.

1993-01-01

Prototype 24 x 25 rectangular array of asynchronous parallel digital processors rapidly finds best path across two-dimensional field, which could be patch of terrain traversed by robotic or military vehicle. Implemented as single-chip very-large-scale integrated circuit. Excepting processors on edges, each processor communicates with four nearest neighbors along paths representing travel to north, south, east, and west. Each processor contains delay generator in form of 8-bit ripple counter, preset to 1 of 256 possible values. Operation begins with choice of processor representing starting point. Transmits signals to nearest neighbor processors, which retransmits to other neighboring processors, and process repeats until signals propagated across entire field.

Programmable Automated Welding System (PAWS)

NASA Technical Reports Server (NTRS)

Kline, Martin D.

1994-01-01

An ambitious project to develop an advanced, automated welding system is being funded as part of the Navy Joining Center with Babcock & Wilcox as the prime integrator. This program, the Programmable Automated Welding System (PAWS), involves the integration of both planning and real-time control activities. Planning functions include the development of a graphical decision support system within a standard, portable environment. Real-time control functions include the development of a modular, intelligent, real-time control system and the integration of a number of welding process sensors. This paper presents each of these components of the PAWS and discusses how they can be utilized to automate the welding operation.

Processor Would Find Best Paths On Map

NASA Technical Reports Server (NTRS)

Eberhardt, Silvio P.

1990-01-01

Proposed very-large-scale integrated (VLSI) circuit image-data processor finds path of least cost from specified origin to any destination on map. Cost of traversal assigned to each picture element of map. Path of least cost from originating picture element to every other picture element computed as path that preserves as much as possible of signal transmitted by originating picture element. Dedicated microprocessor at each picture element stores cost of traversal and performs its share of computations of paths of least cost. Least-cost-path problem occurs in research, military maneuvers, and in planning routes of vehicles.

Automated telescope scheduling

NASA Technical Reports Server (NTRS)

Johnston, Mark D.

1988-01-01

With the ever increasing level of automation of astronomical telescopes the benefits and feasibility of automated planning and scheduling are becoming more apparent. Improved efficiency and increased overall telescope utilization are the most obvious goals. Automated scheduling at some level has been done for several satellite observatories, but the requirements on these systems were much less stringent than on modern ground or satellite observatories. The scheduling problem is particularly acute for Hubble Space Telescope: virtually all observations must be planned in excruciating detail weeks to months in advance. Space Telescope Science Institute has recently made significant progress on the scheduling problem by exploiting state-of-the-art artificial intelligence software technology. What is especially interesting is that this effort has already yielded software that is well suited to scheduling groundbased telescopes, including the problem of optimizing the coordinated scheduling of more than one telescope.

Advanced automation for in-space vehicle processing

NASA Technical Reports Server (NTRS)

Sklar, Michael; Wegerif, D.

1990-01-01

The primary objective of this 3-year planned study is to assure that the fully evolved Space Station Freedom (SSF) can support automated processing of exploratory mission vehicles. Current study assessments show that required extravehicular activity (EVA) and to some extent intravehicular activity (IVA) manpower requirements for required processing tasks far exceeds the available manpower. Furthermore, many processing tasks are either hazardous operations or they exceed EVA capability. Thus, automation is essential for SSF transportation node functionality. Here, advanced automation represents the replacement of human performed tasks beyond the planned baseline automated tasks. Both physical tasks such as manipulation, assembly and actuation, and cognitive tasks such as visual inspection, monitoring and diagnosis, and task planning are considered. During this first year of activity both the Phobos/Gateway Mars Expedition and Lunar Evolution missions proposed by the Office of Exploration have been evaluated. A methodology for choosing optimal tasks to be automated has been developed. Processing tasks for both missions have been ranked on the basis of automation potential. The underlying concept in evaluating and describing processing tasks has been the use of a common set of 'Primitive' task descriptions. Primitive or standard tasks have been developed both for manual or crew processing and automated machine processing.

Automated Planning of Science Products Based on Nadir Overflights and Alerts for Onboard and Ground Processing

NASA Technical Reports Server (NTRS)

Chien, Steve A.; McLaren, David A.; Rabideau, Gregg R.; Mandl, Daniel; Hengemihle, Jerry

2013-01-01

A set of automated planning algorithms is the current operations baseline approach for the Intelligent Payload Module (IPM) of the proposed Hyper spectral Infrared Imager (HyspIRI) mission. For this operations concept, there are only local (e.g. non-depletable) operations constraints, such as real-time downlink and onboard memory, and the forward sweeping algorithm is optimal for determining which science products should be generated onboard and on ground based on geographical overflights, science priorities, alerts, requests, and onboard and ground processing constraints. This automated planning approach was developed for the HyspIRI IPM concept. The HyspIRI IPM is proposed to use an X-band Direct Broadcast (DB) capability that would enable data to be delivered to ground stations virtually as it is acquired. However, the HyspIRI VSWIR and TIR instruments will produce approximately 1 Gbps data, while the DB capability is 15 Mbps for a approx. =60X oversubscription. In order to address this mismatch, this innovation determines which data to downlink based on both the type of surface the spacecraft is overflying, and the onboard processing of data to detect events. For example, when the spacecraft is overflying Polar Regions, it might downlink a snow/ice product. Additionally, the onboard software will search for thermal signatures indicative of a volcanic event or wild fire and downlink summary information (extent, spectra) when detected, thereby reducing data volume. The planning system described above automatically generated the IPM mission plan based on requested products, the overflight regions, and available resources.

Automation and robotics

NASA Technical Reports Server (NTRS)

Montemerlo, Melvin

1988-01-01

The Autonomous Systems focus on the automation of control systems for the Space Station and mission operations. Telerobotics focuses on automation for in-space servicing, assembly, and repair. The Autonomous Systems and Telerobotics each have a planned sequence of integrated demonstrations showing the evolutionary advance of the state-of-the-art. Progress is briefly described for each area of concern.

Visual terrain mapping for traversable path planning of mobile robots

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir; Amrani, Rachida; Tunstel, Edward W.

2004-10-01

In this paper, we have primarily discussed technical challenges and navigational skill requirements of mobile robots for traversability path planning in natural terrain environments similar to Mars surface terrains. We have described different methods for detection of salient terrain features based on imaging texture analysis techniques. We have also presented three competing techniques for terrain traversability assessment of mobile robots navigating in unstructured natural terrain environments. These three techniques include: a rule-based terrain classifier, a neural network-based terrain classifier, and a fuzzy-logic terrain classifier. Each proposed terrain classifier divides a region of natural terrain into finite sub-terrain regions and classifies terrain condition exclusively within each sub-terrain region based on terrain visual clues. The Kalman Filtering technique is applied for aggregative fusion of sub-terrain assessment results. The last two terrain classifiers are shown to have remarkable capability for terrain traversability assessment of natural terrains. We have conducted a comparative performance evaluation of all three terrain classifiers and presented the results in this paper.

Automating Space Station operations planning

NASA Technical Reports Server (NTRS)

Ziemer, Kathleen A.

1989-01-01

The development and implementation of the operations planning processes for the Space Station are discussed. A three level planning process, consisting of strategic, tactical, and execution level planning, is being developed. The integration of the planning procedures into a tactical planning system is examined and the planning phases are illustrated.

76 FR 34246 - Automated Commercial Environment (ACE); Announcement of National Customs Automation Program Test...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-13

... CBP with authority to conduct limited test programs or procedures designed to evaluate planned... aspects of this test, including the design, conduct and implementation of the test, in order to determine... Environment (ACE); Announcement of National Customs Automation Program Test of Automated Procedures for In...

Funding for Library Automation.

ERIC Educational Resources Information Center

Thompson, Ronelle K. H.

This paper provides a brief overview of planning and implementing a project to fund library automation. It is suggested that: (1) proposal budgets should include all costs of a project, such as furniture needed for computer terminals, costs for modifying library procedures, initial supplies, or ongoing maintenance; (2) automation does not save…

Optimal guidance with obstacle avoidance for nap-of-the-earth flight

NASA Technical Reports Server (NTRS)

Pekelsma, Nicholas J.

1988-01-01

The development of automatic guidance is discussed for helicopter Nap-of-the-Earth (NOE) and near-NOE flight. It deals with algorithm refinements relating to automated real-time flight path planning and to mission planning. With regard to path planning, it relates rotorcraft trajectory characteristics to the NOE computation scheme and addresses real-time computing issues and both ride quality issues and pilot-vehicle interfaces. The automated mission planning algorithm refinements include route optimization, automatic waypoint generation, interactive applications, and provisions for integrating the results into the real-time path planning software. A microcomputer based mission planning workstation was developed and is described. Further, the application of Defense Mapping Agency (DMA) digital terrain to both the mission planning workstation and to automatic guidance is both discussed and illustrated.

MR-based real time path planning for cardiac operations with transapical access.

PubMed

Yeniaras, Erol; Navkar, Nikhil V; Sonmez, Ahmet E; Shah, Dipan J; Deng, Zhigang; Tsekos, Nikolaos V

2011-01-01

Minimally invasive surgeries (MIS) have been perpetually evolving due to their potential high impact on improving patient management and overall cost effectiveness. Currently, MIS are further strengthened by the incorporation of magnetic resonance imaging (MRI) for amended visualization and high precision. Motivated by the fact that real-time MRI is emerging as a feasible modality especially for guiding interventions and surgeries in the beating heart; in this paper we introduce a real-time path planning algorithm for intracardiac procedures. Our approach creates a volumetric safety zone inside a beating heart and updates it on-the-fly using real-time MRI during the deployment of a robotic device. In order to prove the concept and assess the feasibility of the introduced method, a realistic operational scenario of transapical aortic valve replacement in a beating heart is chosen as the virtual case study.

PathFinder: reconstruction and dynamic visualization of metabolic pathways.

PubMed

Goesmann, Alexander; Haubrock, Martin; Meyer, Folker; Kalinowski, Jörn; Giegerich, Robert

2002-01-01

Beyond methods for a gene-wise annotation and analysis of sequenced genomes new automated methods for functional analysis on a higher level are needed. The identification of realized metabolic pathways provides valuable information on gene expression and regulation. Detection of incomplete pathways helps to improve a constantly evolving genome annotation or discover alternative biochemical pathways. To utilize automated genome analysis on the level of metabolic pathways new methods for the dynamic representation and visualization of pathways are needed. PathFinder is a tool for the dynamic visualization of metabolic pathways based on annotation data. Pathways are represented as directed acyclic graphs, graph layout algorithms accomplish the dynamic drawing and visualization of the metabolic maps. A more detailed analysis of the input data on the level of biochemical pathways helps to identify genes and detect improper parts of annotations. As an Relational Database Management System (RDBMS) based internet application PathFinder reads a list of EC-numbers or a given annotation in EMBL- or Genbank-format and dynamically generates pathway graphs.

Motion Planning of Two Stacker Cranes in a Large-Scale Automated Storage/Retrieval System

NASA Astrophysics Data System (ADS)

Kung, Yiheng; Kobayashi, Yoshimasa; Higashi, Toshimitsu; Ota, Jun

We propose a method for reducing the computational time of motion planning for stacker cranes. Most automated storage/retrieval systems (AS/RSs) are only equipped with one stacker crane. However, this is logistically challenging, and greater work efficiency in warehouses, such as those using two stacker cranes, is required. In this paper, a warehouse with two stacker cranes working simultaneously is proposed. Unlike warehouses with only one crane, trajectory planning in those with two cranes is very difficult. Since there are two cranes working together, a proper trajectory must be considered to avoid collision. However, verifying collisions is complicated and requires a considerable amount of computational time. As transport work in AS/RSs occurs randomly, motion planning cannot be conducted in advance. Planning an appropriate trajectory within a restricted duration would be a difficult task. We thereby address the current problem of motion planning requiring extensive calculation time. As a solution, we propose a “free-step” to simplify the procedure of collision verification and reduce the computational time. On the other hand, we proposed a method to reschedule the order of collision verification in order to find an appropriate trajectory in less time. By the proposed method, we reduce the calculation time to less than 1/300 of that achieved in former research.

Energy Optimal Path Planning: Integrating Coastal Ocean Modelling with Optimal Control

NASA Astrophysics Data System (ADS)

Subramani, D. N.; Haley, P. J., Jr.; Lermusiaux, P. F. J.

2016-02-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. To set up the energy optimization, the relative vehicle speed and headings are considered to be stochastic, and new stochastic Dynamically Orthogonal (DO) level-set equations that govern their stochastic time-optimal reachability fronts are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. The accuracy and efficiency of the DO level-set equations for solving the governing stochastic level-set reachability fronts are quantitatively assessed, including comparisons with independent semi-analytical solutions. Energy-optimal missions are studied in wind-driven barotropic quasi-geostrophic double-gyre circulations, and in realistic data-assimilative re-analyses of multiscale coastal ocean flows. The latter re-analyses are obtained from multi-resolution 2-way nested primitive-equation simulations of tidal-to-mesoscale dynamics in the Middle Atlantic Bight and Shelbreak Front region. The effects of tidal currents, strong wind events, coastal jets, and shelfbreak fronts on the energy-optimal paths are illustrated and quantified. Results showcase the opportunities for longer-duration missions that intelligently utilize the ocean environment to save energy, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

Path planning and execution monitoring for a planetary rover

NASA Technical Reports Server (NTRS)

Gat, Erann; Slack, Marc G.; Miller, David P.; Firby, R. James

1990-01-01

A path planner and an execution monitoring planner that will enable the rover to navigate to its various destinations safely and correctly while detecting and avoiding hazards are described. An overview of the complete architecture is given. Implementation and testbeds are described. The robot can detect unforseen obstacles and take appropriate action. This includes having the rover back away from the hazard and mark the area as untraversable in the in the rover's internal map. The experiments have consisted of paths roughly 20 m in length. The architecture works with a large variety of rover configurations with different kinematic constraints.

Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

NASA Astrophysics Data System (ADS)

Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok

2016-05-01

This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.

WE-FG-201-02: Automated Treatment Planning for Low-Resource Settings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Court, L.

Many low- and middle-income countries lack the resources and services to manage cancer, from screening and diagnosis to radiation therapy planning, treatment and quality assurance. The challenges in upgrading or introducing the needed services are enormous, and include severe shortages in equipment and trained staff. In this symposium, we will describe examples of technology and scientific research that have the potential to impact all these areas. These include: (1) the development of high-quality/low-cost colposcopes for cervical cancer screening, (2) the application of automated radiotherapy treatment planning to reduce staffing shortages, (3) the development of a novel radiotherapy treatment unit, andmore » (4) utilizing a cloud-based infrastructure to facilitate collaboration and QA. Learning Objectives: Understand some of the issues in cancer care in low- resource environments, including shortages in staff and equipment, and inadequate physical infrastructure for advanced radiotherapy. Understand the challenges in developing and deploying diagnostic and treatment devices and services for low-resource environments. Understand some of the emerging technological solutions for cancer management in LMICs. NCI; L. Court, NIH, Varian, Elekta; I. Feain, Ilana Feain is founder and CTO of Nano-X Pty Ltd.« less

A Comparison of Two Path Planners for Planetary Rovers

NASA Technical Reports Server (NTRS)

Tarokh, M.; Shiller, Z.; Hayati, S.

1999-01-01

The paper presents two path planners suitable for planetary rovers. The first is based on fuzzy description of the terrain, and genetic algorithm to find a traversable path in a rugged terrain. The second planner uses a global optimization method with a cost function that is the path distance divided by the velocity limit obtained from the consideration of the rover static and dynamic stability. A description of both methods is provided, and the results of paths produced are given which show the effectiveness of the path planners in finding near optimal paths. The features of the methods and their suitability and application for rover path planning are compared

Application of heuristic satellite plan synthesis algorithms to requirements of the WARC-88 allotment plan

NASA Technical Reports Server (NTRS)

Heyward, Ann O.; Reilly, Charles H.; Walton, Eric K.; Mata, Fernando; Olen, Carl

1990-01-01

Creation of an Allotment Plan for the Fixed Satellite Service at the 1988 Space World Administrative Radio Conference (WARC) represented a complex satellite plan synthesis problem, involving a large number of planned and existing systems. Solutions to this problem at WARC-88 required the use of both automated and manual procedures to develop an acceptable set of system positions. Development of an Allotment Plan may also be attempted through solution of an optimization problem, known as the Satellite Location Problem (SLP). Three automated heuristic procedures, developed specifically to solve SLP, are presented. The heuristics are then applied to two specific WARC-88 scenarios. Solutions resulting from the fully automated heuristics are then compared with solutions obtained at WARC-88 through a combination of both automated and manual planning efforts.

Planning for the Automation of School Library Media Centers.

ERIC Educational Resources Information Center

Caffarella, Edward P.

1996-01-01

Geared for school library media specialists whose centers are in the early stages of automation or conversion to a new system, this article focuses on major components of media center automation: circulation control; online public access catalogs; machine readable cataloging; retrospective conversion of print catalog cards; and computer networks…

Automated process planning system

NASA Technical Reports Server (NTRS)

Mann, W.

1978-01-01

Program helps process engineers set up manufacturing plans for machined parts. System allows one to develop and store library of similar parts characteristics, as related to particular facility. Information is then used in interactive system to help develop manufacturing plans that meet required standards.

Automated microwave ablation therapy planning with single and multiple entry points

NASA Astrophysics Data System (ADS)

Liu, Sheena X.; Dalal, Sandeep; Kruecker, Jochen

2012-02-01

Microwave ablation (MWA) has become a recommended treatment modality for interventional cancer treatment. Compared with radiofrequency ablation (RFA), MWA provides more rapid and larger-volume tissue heating. It allows simultaneous ablation from different entry points and allows users to change the ablation size by controlling the power/time parameters. Ablation planning systems have been proposed in the past, mainly addressing the needs for RFA procedures. Thus a planning system addressing MWA-specific parameters and workflows is highly desirable to help physicians achieve better microwave ablation results. In this paper, we design and implement an automated MWA planning system that provides precise probe locations for complete coverage of tumor and margin. We model the thermal ablation lesion as an ellipsoidal object with three known radii varying with the duration of the ablation and the power supplied to the probe. The search for the best ablation coverage can be seen as an iterative optimization problem. The ablation centers are steered toward the location which minimizes both un-ablated tumor tissue and the collateral damage caused to the healthy tissue. We assess the performance of our algorithm using simulated lesions with known "ground truth" optimal coverage. The Mean Localization Error (MLE) between the computed ablation center in 3D and the ground truth ablation center achieves 1.75mm (Standard deviation of the mean (STD): 0.69mm). The Mean Radial Error (MRE) which is estimated by comparing the computed ablation radii with the ground truth radii reaches 0.64mm (STD: 0.43mm). These preliminary results demonstrate the accuracy and robustness of the described planning algorithm.

SU-D-BRD-06: Automated Population-Based Planning for Whole Brain Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schreibmann, E; Fox, T; Crocker, I

2014-06-01

Purpose: Treatment planning for whole brain radiation treatment is technically a simple process but in practice it takes valuable clinical time of repetitive and tedious tasks. This report presents a method that automatically segments the relevant target and normal tissues and creates a treatment plan in only a few minutes after patient simulation. Methods: Segmentation is performed automatically through morphological operations on the soft tissue. The treatment plan is generated by searching a database of previous cases for patients with similar anatomy. In this search, each database case is ranked in terms of similarity using a customized metric designed formore » sensitivity by including only geometrical changes that affect the dose distribution. The database case with the best match is automatically modified to replace relevant patient info and isocenter position while maintaining original beam and MLC settings. Results: Fifteen patients were used to validate the method. In each of these cases the anatomy was accurately segmented to mean Dice coefficients of 0.970 ± 0.008 for the brain, 0.846 ± 0.009 for the eyes and 0.672 ± 0.111 for the lens as compared to clinical segmentations. Each case was then subsequently matched against a database of 70 validated treatment plans and the best matching plan (termed auto-planned), was compared retrospectively with the clinical plans in terms of brain coverage and maximum doses to critical structures. Maximum doses were reduced by a maximum of 20.809 Gy for the left eye (mean 3.533), by 13.352 (1.311) for the right eye, and by 27.471 (4.856), 25.218 (6.315) for the left and right lens. Time from simulation to auto-plan was 3-4 minutes. Conclusion: Automated database- based matching is an alternative to classical treatment planning that improves quality while providing a cost—effective solution to planning through modifying previous validated plans to match a current patient's anatomy.« less

An automated integration-free path-integral method based on Kleinert's variational perturbation theory

NASA Astrophysics Data System (ADS)

Wong, Kin-Yiu; Gao, Jiali

2007-12-01

Based on Kleinert's variational perturbation (KP) theory [Path Integrals in Quantum Mechanics, Statistics, Polymer Physics, and Financial Markets, 3rd ed. (World Scientific, Singapore, 2004)], we present an analytic path-integral approach for computing the effective centroid potential. The approach enables the KP theory to be applied to any realistic systems beyond the first-order perturbation (i.e., the original Feynman-Kleinert [Phys. Rev. A 34, 5080 (1986)] variational method). Accurate values are obtained for several systems in which exact quantum results are known. Furthermore, the computed kinetic isotope effects for a series of proton transfer reactions, in which the potential energy surfaces are evaluated by density-functional theory, are in good accordance with experiments. We hope that our method could be used by non-path-integral experts or experimentalists as a "black box" for any given system.

Path to a Research Plan

NASA Technical Reports Server (NTRS)

Chiaramonte, Fran

2003-01-01

This viewgraph presentation discusses the status and goals for the NASA OBPR Physical Science Research Program. The following text was used to summarize the presentation. The OBPR Physical Sciences Research program has been comprehensively reviewed and endorsed by National Research Council. The value and need for the research have been re-affirmed. The research program has been prioritized and resource re-allocations have been carried out through an OBPR-wide process. An increasing emphasis on strategic, mission-oriented research is planned. The program will strive to maintain a balance between strategic and fundamental research. A feasible ISS flight research program fitting within the budgetary and ISS resource envelopes has been formulated for the near term (2003-2007). The current ISS research program will be significantly strengthened starting 2005 by using discipline dedicated research facility racks. A research re-planning effort has been initiated and will include active participation from the research community in the next few months. The research re-planning effort will poise PSR to increase ISS research utilization for a potential enhancement beyond ISS IP Core Complete. The Physical Sciences research program readily integrates the cross-disciplinary requirements of the NASA and OBPR strategic objectives. Each fundamental research thrust will develop a roadmap through technical workshops and Discipline Working Groups (DWGs). Most fundamental research thrusts will involve cross-disciplinary efforts. A Technology Roadmap will guide the Strategic Research for Exploration thrust. The Research Plan will integrate and coordinate fundamental Research Thrusts Roadmaps with the Technology Roadmap. The Technology Roadmap will be developed in coordination with other OBPR programs as well as other Enterprise (R,S,M,N). International Partners will contribute to the roadmaps and through research coordination. The research plan will be vetted with the discipline

A plan for time-phased incorporation of automation and robotics on the US space station

NASA Technical Reports Server (NTRS)

Purves, R. B.; Lin, P. S.; Fisher, E. M., Jr.

1988-01-01

A plan for the incorporation of Automation and Robotics technology on the Space Station is presented. The time phased introduction of twenty two selected candidates is set forth in accordance with a technology development forecast. Twenty candidates were chosed primarily for their potential to relieve the crew of mundane or dangerous operations and maintenance burdens, thus freeing crew time for mission duties and enhancing safety. Two candidates were chosen based on a potential for increasing the productivity of laboratory experiments and thus directly enhancing the scientific value of the Space Station. A technology assessment for each candidate investigates present state of the art, development timelines including space qualification considerations, and potential for technology transfer to earth applications. Each candidate is evaluated using a crew workload model driven by crew size, number of pressurized U.S. modules and external payloads, which makes it possible to assess the impact of automation during a growth scenario. Costs for each increment of implementation are estimated and accumulated.

Spreading paths in partially observed social networks

NASA Astrophysics Data System (ADS)

Onnela, Jukka-Pekka; Christakis, Nicholas A.

2012-03-01

Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.

Spreading paths in partially observed social networks.

PubMed

Onnela, Jukka-Pekka; Christakis, Nicholas A

2012-03-01

Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using static, structurally realistic social networks as platforms for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.

All new custom path photo book creation

NASA Astrophysics Data System (ADS)

Wang, Wiley; Muzzolini, Russ

2012-03-01

In this paper, we present an all new custom path to allow consumers to have full control to their photos and the format of their books, while providing them with guidance to make their creation fast and easy. The users can choose to fully automate the initial creation, and then customize every page. The system manage many design themes along with numerous design elements, such as layouts, backgrounds, embellishments and pattern bands. The users can also utilize photos from multiple sources including their computers, Shutterfly accounts, Shutterfly Share sites and Facebook. The users can also use a photo as background, add, move and resize photos and text - putting what they want where they want instead of being confined to templates. The new path allows users to add embellishments anywhere in the book, and the high-performance platform can support up to 1,000 photos per book and up to 25 pictures per page. The path offers either Smart Autofill or Storyboard features allowing customers to populate their books with photos so they can add captions and customize the pages.

The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan

2015-11-15

Purpose: Significant dosimetric benefits had been previously demonstrated in highly noncoplanar treatment plans. In this study, the authors developed and verified an individualized collision model for the purpose of delivering highly noncoplanar radiotherapy and tested the feasibility of total delivery automation with Varian TrueBeam developer mode. Methods: A hand-held 3D scanner was used to capture the surfaces of an anthropomorphic phantom and a human subject, which were positioned with a computer-aided design model of a TrueBeam machine to create a detailed virtual geometrical collision model. The collision model included gantry, collimator, and couch motion degrees of freedom. The accuracy ofmore » the 3D scanner was validated by scanning a rigid cubical phantom with known dimensions. The collision model was then validated by generating 300 linear accelerator orientations corresponding to 300 gantry-to-couch and gantry-to-phantom distances, and comparing the corresponding distance measurements to their corresponding models. The linear accelerator orientations reflected uniformly sampled noncoplanar beam angles to the head, lung, and prostate. The distance discrepancies between measurements on the physical and virtual systems were used to estimate treatment-site-specific safety buffer distances with 0.1%, 0.01%, and 0.001% probability of collision between the gantry and couch or phantom. Plans containing 20 noncoplanar beams to the brain, lung, and prostate optimized via an in-house noncoplanar radiotherapy platform were converted into XML script for automated delivery and the entire delivery was recorded and timed to demonstrate the feasibility of automated delivery. Results: The 3D scanner measured the dimension of the 14 cm cubic phantom within 0.5 mm. The maximal absolute discrepancy between machine and model measurements for gantry-to-couch and gantry-to-phantom was 0.95 and 2.97 cm, respectively. The reduced accuracy of gantry-to-phantom measurements

The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery.

PubMed

Yu, Victoria Y; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A; Sheng, Ke

2015-11-01

Significant dosimetric benefits had been previously demonstrated in highly noncoplanar treatment plans. In this study, the authors developed and verified an individualized collision model for the purpose of delivering highly noncoplanar radiotherapy and tested the feasibility of total delivery automation with Varian TrueBeam developer mode. A hand-held 3D scanner was used to capture the surfaces of an anthropomorphic phantom and a human subject, which were positioned with a computer-aided design model of a TrueBeam machine to create a detailed virtual geometrical collision model. The collision model included gantry, collimator, and couch motion degrees of freedom. The accuracy of the 3D scanner was validated by scanning a rigid cubical phantom with known dimensions. The collision model was then validated by generating 300 linear accelerator orientations corresponding to 300 gantry-to-couch and gantry-to-phantom distances, and comparing the corresponding distance measurements to their corresponding models. The linear accelerator orientations reflected uniformly sampled noncoplanar beam angles to the head, lung, and prostate. The distance discrepancies between measurements on the physical and virtual systems were used to estimate treatment-site-specific safety buffer distances with 0.1%, 0.01%, and 0.001% probability of collision between the gantry and couch or phantom. Plans containing 20 noncoplanar beams to the brain, lung, and prostate optimized via an in-house noncoplanar radiotherapy platform were converted into XML script for automated delivery and the entire delivery was recorded and timed to demonstrate the feasibility of automated delivery. The 3D scanner measured the dimension of the 14 cm cubic phantom within 0.5 mm. The maximal absolute discrepancy between machine and model measurements for gantry-to-couch and gantry-to-phantom was 0.95 and 2.97 cm, respectively. The reduced accuracy of gantry-to-phantom measurements was attributed to phantom setup

The development and verification of a highly accurate collision prediction model for automated noncoplanar plan delivery

PubMed Central

Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke

2015-01-01

Purpose: Significant dosimetric benefits had been previously demonstrated in highly noncoplanar treatment plans. In this study, the authors developed and verified an individualized collision model for the purpose of delivering highly noncoplanar radiotherapy and tested the feasibility of total delivery automation with Varian TrueBeam developer mode. Methods: A hand-held 3D scanner was used to capture the surfaces of an anthropomorphic phantom and a human subject, which were positioned with a computer-aided design model of a TrueBeam machine to create a detailed virtual geometrical collision model. The collision model included gantry, collimator, and couch motion degrees of freedom. The accuracy of the 3D scanner was validated by scanning a rigid cubical phantom with known dimensions. The collision model was then validated by generating 300 linear accelerator orientations corresponding to 300 gantry-to-couch and gantry-to-phantom distances, and comparing the corresponding distance measurements to their corresponding models. The linear accelerator orientations reflected uniformly sampled noncoplanar beam angles to the head, lung, and prostate. The distance discrepancies between measurements on the physical and virtual systems were used to estimate treatment-site-specific safety buffer distances with 0.1%, 0.01%, and 0.001% probability of collision between the gantry and couch or phantom. Plans containing 20 noncoplanar beams to the brain, lung, and prostate optimized via an in-house noncoplanar radiotherapy platform were converted into XML script for automated delivery and the entire delivery was recorded and timed to demonstrate the feasibility of automated delivery. Results: The 3D scanner measured the dimension of the 14 cm cubic phantom within 0.5 mm. The maximal absolute discrepancy between machine and model measurements for gantry-to-couch and gantry-to-phantom was 0.95 and 2.97 cm, respectively. The reduced accuracy of gantry-to-phantom measurements was

Path Planning For A Class Of Cutting Operations

NASA Astrophysics Data System (ADS)

Tavora, Jose

1989-03-01

Optimizing processing time in some contour-cutting operations requires solving the so-called no-load path problem. This problem is formulated and an approximate resolution method (based on heuristic search techniques) is described. Results for real-life instances (clothing layouts in the apparel industry) are presented and evaluated.

Automated Attitude Sensor Calibration: Progress and Plans

NASA Technical Reports Server (NTRS)

Sedlak, Joseph; Hashmall, Joseph

2004-01-01

This paper describes ongoing work a NASA/Goddard Space Flight Center to improve the quality of spacecraft attitude sensor calibration and reduce costs by automating parts of the calibration process. The new calibration software can autonomously preview data quality over a given time span, select a subset of the data for processing, perform the requested calibration, and output a report. This level of automation is currently being implemented for two specific applications: inertial reference unit (IRU) calibration and sensor alignment calibration. The IRU calibration utility makes use of a sequential version of the Davenport algorithm. This utility has been successfully tested with simulated and actual flight data. The alignment calibration is still in the early testing stage. Both utilities will be incorporated into the institutional attitude ground support system.

Part-task training in the context of automation: current and future directions.

PubMed

Gutzwiller, Robert S; Clegg, Benjamin A; Blitch, John G

2013-01-01

Automation often elicits a divide-and-conquer outlook. By definition, automation has been suggested to assume control over a part or whole task that was previously performed by a human (Parasuraman & Riley, 1997). When such notions of automation are taken as grounds for training, they readily invoke a part-task training (PTT) approach. This article outlines broad functions of automation as a source of PTT and reviews the PTT literature, focusing on the potential benefits and costs related to using automation as a mechanism for PTT. The article reviews some past work in this area and suggests a path to move beyond the type of work captured by the "automation as PTT" framework. An illustrative experiment shows how automation in training and PTT are actually separable issues. PTT with automation has some utility but ultimately remains an unsatisfactory framework for the future broad potential of automation during training, and we suggest that a new conceptualization is needed.

Human-Automation Collaborative RRT for UAV Mission Path Planning

DTIC Science & Technology

2010-06-01

5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS( ES ) Massachusetts Institute of Technology,Department of... ES ) 10. SPONSOR/MONITOR’S ACRONYM(S) 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release...También quiero agradecerle a mi madre, Gloria, mi hermana, Glorianna, mi padre, mis abuelitos, y mis tios por todo el amor y apoyo que me han dado toda

Near real-time automated dose restoration in IMPT to compensate for daily tissue density variations in prostate cancer

NASA Astrophysics Data System (ADS)

Jagt, Thyrza; Breedveld, Sebastiaan; van de Water, Steven; Heijmen, Ben; Hoogeman, Mischa

2017-06-01

Proton therapy is very sensitive to daily density changes along the pencil beam paths. The purpose of this study is to develop and evaluate an automated method for adaptation of IMPT plans to compensate for these daily tissue density variations. A two-step restoration method for ‘densities-of-the-day’ was created: (1) restoration of spot positions (Bragg peaks) by adapting the energy of each pencil beam to the new water equivalent path length; and (2) re-optimization of pencil beam weights by minimizing the dosimetric difference with the planned dose distribution, using a fast and exact quadratic solver. The method was developed and evaluated using 8-10 repeat CT scans of 10 prostate cancer patients. Experiments demonstrated that giving a high weight to the PTV in the re-optimization resulted in clinically acceptable restorations. For all scans we obtained V 95%  ⩾  98% and V 107%  ⩽  2%. For the bladder, the differences between the restored and the intended treatment plan were below  +2 Gy and  +2%-point. The rectum differences were below  +2 Gy and  +2%-point for 90% of the scans. In the remaining scans the rectum was filled with air, which partly overlapped with the PTV. The air cavity distorted the Bragg peak resulting in less favorable rectum doses.

A PLM-based automated inspection planning system for coordinate measuring machine

NASA Astrophysics Data System (ADS)

Zhao, Haibin; Wang, Junying; Wang, Boxiong; Wang, Jianmei; Chen, Huacheng

2006-11-01

With rapid progress of Product Lifecycle Management (PLM) in manufacturing industry, automatic generation of inspection planning of product and the integration with other activities in product lifecycle play important roles in quality control. But the techniques for these purposes are laggard comparing with techniques of CAD/CAM. Therefore, an automatic inspection planning system for Coordinate Measuring Machine (CMM) was developed to improve the automatization of measuring based on the integration of inspection system in PLM. Feature information representation is achieved based on a PLM canter database; measuring strategy is optimized through the integration of multi-sensors; reasonable number and distribution of inspection points are calculated and designed with the guidance of statistic theory and a synthesis distribution algorithm; a collision avoidance method is proposed to generate non-collision inspection path with high efficiency. Information mapping is performed between Neutral Interchange Files (NIFs), such as STEP, DML, DMIS, XML, etc., to realize information integration with other activities in the product lifecycle like design, manufacturing and inspection execution, etc. Simulation was carried out to demonstrate the feasibility of the proposed system. As a result, the inspection process is becoming simpler and good result can be got based on the integration in PLM.

North Carolina: Statewide Automation and Connectivity Efforts.

ERIC Educational Resources Information Center

Christian, Elaine J., Ed.

1996-01-01

Describes statewide information automation and connectivity efforts in North Carolina. Highlights include Triangle Research Libraries Network Document Delivery System; cooperative networking projects; public library connectivity to the state library; rural access projects; community college automation; K-12 technology plans; electronic government…

National Aeronautics and Space Administration's (NASA) Automated Information Security Handbook

NASA Technical Reports Server (NTRS)

Roback, E.

1991-01-01

The NASA Automated Information Security Handbook provides NASA's overall approach to automated information systems security including discussions of such aspects as: program goals and objectives, assignment of responsibilities, risk assessment, foreign national access, contingency planning and disaster recovery, awareness training, procurement, certification, planning, and special considerations for microcomputers.

Cockpit Adaptive Automation and Pilot Performance

NASA Technical Reports Server (NTRS)

Parasuraman, Raja

2001-01-01

The introduction of high-level automated systems in the aircraft cockpit has provided several benefits, e.g., new capabilities, enhanced operational efficiency, and reduced crew workload. At the same time, conventional 'static' automation has sometimes degraded human operator monitoring performance, increased workload, and reduced situation awareness. Adaptive automation represents an alternative to static automation. In this approach, task allocation between human operators and computer systems is flexible and context-dependent rather than static. Adaptive automation, or adaptive task allocation, is thought to provide for regulation of operator workload and performance, while preserving the benefits of static automation. In previous research we have reported beneficial effects of adaptive automation on the performance of both pilots and non-pilots of flight-related tasks. For adaptive systems to be viable, however, such benefits need to be examined jointly in the context of a single set of tasks. The studies carried out under this project evaluated a systematic method for combining different forms of adaptive automation. A model for effective combination of different forms of adaptive automation, based on matching adaptation to operator workload was proposed and tested. The model was evaluated in studies using IFR-rated pilots flying a general-aviation simulator. Performance, subjective, and physiological (heart rate variability, eye scan-paths) measures of workload were recorded. The studies compared workload-based adaptation to to non-adaptive control conditions and found evidence for systematic benefits of adaptive automation. The research provides an empirical basis for evaluating the effectiveness of adaptive automation in the cockpit. The results contribute to the development of design principles and guidelines for the implementation of adaptive automation in the cockpit, particularly in general aviation, and in other human-machine systems. Project goals

Automated planning of ablation targets in atrial fibrillation treatment

NASA Astrophysics Data System (ADS)

Keustermans, Johannes; De Buck, Stijn; Heidbüchel, Hein; Suetens, Paul

2011-03-01

Catheter based radio-frequency ablation is used as an invasive treatment of atrial fibrillation. This procedure is often guided by the use of 3D anatomical models obtained from CT, MRI or rotational angiography. During the intervention the operator accurately guides the catheter to prespecified target ablation lines. The planning stage, however, can be time consuming and operator dependent which is suboptimal both from a cost and health perspective. Therefore, we present a novel statistical model-based algorithm for locating ablation targets from 3D rotational angiography images. Based on a training data set of 20 patients, consisting of 3D rotational angiography images with 30 manually indicated ablation points, a statistical local appearance and shape model is built. The local appearance model is based on local image descriptors to capture the intensity patterns around each ablation point. The local shape model is constructed by embedding the ablation points in an undirected graph and imposing that each ablation point only interacts with its neighbors. Identifying the ablation points on a new 3D rotational angiography image is performed by proposing a set of possible candidate locations for each ablation point, as such, converting the problem into a labeling problem. The algorithm is validated using a leave-one-out-approach on the training data set, by computing the distance between the ablation lines obtained by the algorithm and the manually identified ablation points. The distance error is equal to 3.8+/-2.9 mm. As ablation lesion size is around 5-7 mm, automated planning of ablation targets by the presented approach is sufficiently accurate.

Task Analysis and Descriptions of Required Job Competencies for Robotics/Automated Systems Technicians. Final Report. Volume 2. Curriculum Planning Guide.

ERIC Educational Resources Information Center

Hull, Daniel M.; Lovett, James E.

This volume of the final report for the Robotics/Automated Systems Technician (RAST) curriculum project is a curriculum planning guide intended for school administrators, faculty, and student counselors/advisors. It includes step-by-step procedures to help institutions evaluate their community's needs and their capabilities to meet these needs in…

A statistical-based scheduling algorithm in automated data path synthesis

NASA Technical Reports Server (NTRS)

Jeon, Byung Wook; Lursinsap, Chidchanok

1992-01-01

In this paper, we propose a new heuristic scheduling algorithm based on the statistical analysis of the cumulative frequency distribution of operations among control steps. It has a tendency of escaping from local minima and therefore reaching a globally optimal solution. The presented algorithm considers the real world constraints such as chained operations, multicycle operations, and pipelined data paths. The result of the experiment shows that it gives optimal solutions, even though it is greedy in nature.

Path-following control of wheeled planetary exploration robots moving on deformable rough terrain.

PubMed

Ding, Liang; Gao, Hai-bo; Deng, Zong-quan; Li, Zhijun; Xia, Ke-rui; Duan, Guang-ren

2014-01-01

The control of planetary rovers, which are high performance mobile robots that move on deformable rough terrain, is a challenging problem. Taking lateral skid into account, this paper presents a rough terrain model and nonholonomic kinematics model for planetary rovers. An approach is proposed in which the reference path is generated according to the planned path by combining look-ahead distance and path updating distance on the basis of the carrot following method. A path-following strategy for wheeled planetary exploration robots incorporating slip compensation is designed. Simulation results of a four-wheeled robot on deformable rough terrain verify that it can be controlled to follow a planned path with good precision, despite the fact that the wheels will obviously skid and slip.

Path-Following Control of Wheeled Planetary Exploration Robots Moving on Deformable Rough Terrain

PubMed Central

Ding, Liang; Gao, Hai-bo; Deng, Zong-quan; Li, Zhijun; Xia, Ke-rui; Duan, Guang-ren

2014-01-01

The control of planetary rovers, which are high performance mobile robots that move on deformable rough terrain, is a challenging problem. Taking lateral skid into account, this paper presents a rough terrain model and nonholonomic kinematics model for planetary rovers. An approach is proposed in which the reference path is generated according to the planned path by combining look-ahead distance and path updating distance on the basis of the carrot following method. A path-following strategy for wheeled planetary exploration robots incorporating slip compensation is designed. Simulation results of a four-wheeled robot on deformable rough terrain verify that it can be controlled to follow a planned path with good precision, despite the fact that the wheels will obviously skid and slip. PMID:24790582

SSTAC/ARTS review of the draft Integrated Technology Plan (ITP). Volume 8: Aerothermodynamics Automation and Robotics (A/R) systems sensors, high-temperature superconductivity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

Viewgraphs of briefings presented at the SSTAC/ARTS review of the draft Integrated Technology Plan (ITP) on aerothermodynamics, automation and robotics systems, sensors, and high-temperature superconductivity are included. Topics covered include: aerothermodynamics; aerobraking; aeroassist flight experiment; entry technology for probes and penetrators; automation and robotics; artificial intelligence; NASA telerobotics program; planetary rover program; science sensor technology; direct detector; submillimeter sensors; laser sensors; passive microwave sensing; active microwave sensing; sensor electronics; sensor optics; coolers and cryogenics; and high temperature superconductivity.

SSTAC/ARTS review of the draft Integrated Technology Plan (ITP). Volume 8: Aerothermodynamics Automation and Robotics (A/R) systems sensors, high-temperature superconductivity

NASA Technical Reports Server (NTRS)

1991-01-01

Viewgraphs of briefings presented at the SSTAC/ARTS review of the draft Integrated Technology Plan (ITP) on aerothermodynamics, automation and robotics systems, sensors, and high-temperature superconductivity are included. Topics covered include: aerothermodynamics; aerobraking; aeroassist flight experiment; entry technology for probes and penetrators; automation and robotics; artificial intelligence; NASA telerobotics program; planetary rover program; science sensor technology; direct detector; submillimeter sensors; laser sensors; passive microwave sensing; active microwave sensing; sensor electronics; sensor optics; coolers and cryogenics; and high temperature superconductivity.

Path optimization with limited sensing ability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kang, Sung Ha, E-mail: kang@math.gatech.edu; Kim, Seong Jun, E-mail: skim396@math.gatech.edu; Zhou, Haomin, E-mail: hmzhou@math.gatech.edu

2015-10-15

We propose a computational strategy to find the optimal path for a mobile sensor with limited coverage to traverse a cluttered region. The goal is to find one of the shortest feasible paths to achieve the complete scan of the environment. We pose the problem in the level set framework, and first consider a related question of placing multiple stationary sensors to obtain the full surveillance of the environment. By connecting the stationary locations using the nearest neighbor strategy, we form the initial guess for the path planning problem of the mobile sensor. Then the path is optimized by reducingmore » its length, via solving a system of ordinary differential equations (ODEs), while maintaining the complete scan of the environment. Furthermore, we use intermittent diffusion, which converts the ODEs into stochastic differential equations (SDEs), to find an optimal path whose length is globally minimal. To improve the computation efficiency, we introduce two techniques, one to remove redundant connecting points to reduce the dimension of the system, and the other to deal with the entangled path so the solution can escape the local traps. Numerical examples are shown to illustrate the effectiveness of the proposed method.« less

Automated IMRT planning with regional optimization using planning scripts

PubMed Central

Wong, Eugene; Bzdusek, Karl; Lock, Michael; Chen, Jeff Z.

2013-01-01

Intensity‐modulated radiation therapy (IMRT) has become a standard technique in radiation therapy for treating different types of cancers. Various class solutions have been developed for simple cases (e.g., localized prostate, whole breast) to generate IMRT plans efficiently. However, for more complex cases (e.g., head and neck, pelvic nodes), it can be time‐consuming for a planner to generate optimized IMRT plans. To generate optimal plans in these more complex cases which generally have multiple target volumes and organs at risk, it is often required to have additional IMRT optimization structures such as dose limiting ring structures, adjust beam geometry, select inverse planning objectives and associated weights, and additional IMRT objectives to reduce cold and hot spots in the dose distribution. These parameters are generally manually adjusted with a repeated trial and error approach during the optimization process. To improve IMRT planning efficiency in these more complex cases, an iterative method that incorporates some of these adjustment processes automatically in a planning script is designed, implemented, and validated. In particular, regional optimization has been implemented in an iterative way to reduce various hot or cold spots during the optimization process that begins with defining and automatic segmentation of hot and cold spots, introducing new objectives and their relative weights into inverse planning, and turn this into an iterative process with termination criteria. The method has been applied to three clinical sites: prostate with pelvic nodes, head and neck, and anal canal cancers, and has shown to reduce IMRT planning time significantly for clinical applications with improved plan quality. The IMRT planning scripts have been used for more than 500 clinical cases. PACS numbers: 87.55.D, 87.55.de PMID:23318393

Geometric Reasoning for Automated Planning

NASA Technical Reports Server (NTRS)

Clement, Bradley J.; Knight, Russell L.; Broderick, Daniel

2012-01-01

An important aspect of mission planning for NASA s operation of the International Space Station is the allocation and management of space for supplies and equipment. The Stowage, Configuration Analysis, and Operations Planning teams collaborate to perform the bulk of that planning. A Geometric Reasoning Engine is developed in a way that can be shared by the teams to optimize item placement in the context of crew planning. The ISS crew spends (at the time of this writing) a third or more of their time moving supplies and equipment around. Better logistical support and optimized packing could make a significant impact on operational efficiency of the ISS. Currently, computational geometry and motion planning do not focus specifically on the optimized orientation and placement of 3D objects based on multiple distance and containment preferences and constraints. The software performs reasoning about the manipulation of 3D solid models in order to maximize an objective function based on distance. It optimizes for 3D orientation and placement. Spatial placement optimization is a general problem and can be applied to object packing or asset relocation.

Using artificial intelligence to automate remittance processing.

PubMed

Adams, W T; Snow, G M; Helmick, P M

1998-06-01

The consolidated business office of the Allegheny Health Education Research Foundation (AHERF), a large integrated healthcare system based in Pittsburgh, Pennsylvania, sought to improve its cash-related business office activities by implementing an automated remittance processing system that uses artificial intelligence. The goal was to create a completely automated system whereby all monies it processed would be tracked, automatically posted, analyzed, monitored, controlled, and reconciled through a central database. Using a phased approach, the automated payment system has become the central repository for all of the remittances for seven of the hospitals in the AHERF system and has allowed for the complete integration of these hospitals' existing billing systems, document imaging system, and intranet, as well as the new automated payment posting, and electronic cash tracking and reconciling systems. For such new technology, which is designed to bring about major change, factors contributing to the project's success were adequate planning, clearly articulated objectives, marketing, end-user acceptance, and post-implementation plan revision.

Navigating the Path to a Biomedical Science Career

NASA Astrophysics Data System (ADS)

Zimmerman, Andrea McNeely

The number of biomedical PhD scientists being trained and graduated far exceeds the number of academic faculty positions and academic research jobs. If this trend is compelling biomedical PhD scientists to increasingly seek career paths outside of academia, then more should be known about their intentions, desires, training experiences, and career path navigation. Therefore, the purpose of this study was to understand the process through which biomedical PhD scientists are trained and supported for navigating future career paths. In addition, the study sought to determine whether career development support efforts and opportunities should be redesigned to account for the proportion of PhD scientists following non-academic career pathways. Guided by the social cognitive career theory (SCCT) framework this study sought to answer the following central research question: How does a southeastern tier 1 research university train and support its biomedical PhD scientists for navigating their career paths? Key findings are: Many factors influence PhD scientists' career sector preference and job search process, but the most influential were relationships with faculty, particularly the mentor advisor; Planned activities are a significant aspect of the training process and provide skills for career success; and Planned activities provided skills necessary for a career, but influential factors directed the career path navigated. Implications for practice and future research are discussed.

Formal language constrained path problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barrett, C.; Jacob, R.; Marathe, M.

1997-07-08

In many path finding problems arising in practice, certain patterns of edge/vertex labels in the labeled graph being traversed are allowed/preferred, while others are disallowed. Motivated by such applications as intermodal transportation planning, the authors investigate the complexity of finding feasible paths in a labeled network, where the mode choice for each traveler is specified by a formal language. The main contributions of this paper include the following: (1) the authors show that the problem of finding a shortest path between a source and destination for a traveler whose mode choice is specified as a context free language is solvablemore » efficiently in polynomial time, when the mode choice is specified as a regular language they provide algorithms with improved space and time bounds; (2) in contrast, they show that the problem of finding simple paths between a source and a given destination is NP-hard, even when restricted to very simple regular expressions and/or very simple graphs; (3) for the class of treewidth bounded graphs, they show that (i) the problem of finding a regular language constrained simple path between source and a destination is solvable in polynomial time and (ii) the extension to finding context free language constrained simple paths is NP-complete. Several extensions of these results are presented in the context of finding shortest paths with additional constraints. These results significantly extend the results in [MW95]. As a corollary of the results, they obtain a polynomial time algorithm for the BEST k-SIMILAR PATH problem studied in [SJB97]. The previous best algorithm was given by [SJB97] and takes exponential time in the worst case.« less

Manned spacecraft automation and robotics

NASA Technical Reports Server (NTRS)

Erickson, Jon D.

1987-01-01

The Space Station holds promise of being a showcase user and driver of advanced automation and robotics technology. The author addresses the advances in automation and robotics from the Space Shuttle - with its high-reliability redundancy management and fault tolerance design and its remote manipulator system - to the projected knowledge-based systems for monitoring, control, fault diagnosis, planning, and scheduling, and the telerobotic systems of the future Space Station.

Automating Small Libraries.

ERIC Educational Resources Information Center

Swan, James

1996-01-01

Presents a four-phase plan for small libraries strategizing for automation: inventory and weeding, data conversion, implementation, and enhancements. Other topics include selecting a system, MARC records, compatibility, ease of use, industry standards, searching capabilities, support services, system security, screen displays, circulation modules,…

Laboratory automation: trajectory, technology, and tactics.

PubMed

Markin, R S; Whalen, S A

2000-05-01

Laboratory automation is in its infancy, following a path parallel to the development of laboratory information systems in the late 1970s and early 1980s. Changes on the horizon in healthcare and clinical laboratory service that affect the delivery of laboratory results include the increasing age of the population in North America, the implementation of the Balanced Budget Act (1997), and the creation of disease management companies. Major technology drivers include outcomes optimization and phenotypically targeted drugs. Constant cost pressures in the clinical laboratory have forced diagnostic manufacturers into less than optimal profitability states. Laboratory automation can be a tool for the improvement of laboratory services and may decrease costs. The key to improvement of laboratory services is implementation of the correct automation technology. The design of this technology should be driven by required functionality. Automation design issues should be centered on the understanding of the laboratory and its relationship to healthcare delivery and the business and operational processes in the clinical laboratory. Automation design philosophy has evolved from a hardware-based approach to a software-based approach. Process control software to support repeat testing, reflex testing, and transportation management, and overall computer-integrated manufacturing approaches to laboratory automation implementation are rapidly expanding areas. It is clear that hardware and software are functionally interdependent and that the interface between the laboratory automation system and the laboratory information system is a key component. The cost-effectiveness of automation solutions suggested by vendors, however, has been difficult to evaluate because the number of automation installations are few and the precision with which operational data have been collected to determine payback is suboptimal. The trend in automation has moved from total laboratory automation to a

Automated Sequence Generation Process and Software

NASA Technical Reports Server (NTRS)

Gladden, Roy

2007-01-01

"Automated sequence generation" (autogen) signifies both a process and software used to automatically generate sequences of commands to operate various spacecraft. The autogen software comprises the autogen script plus the Activity Plan Generator (APGEN) program. APGEN can be used for planning missions and command sequences.

Stage Evolution of Office Automation Technological Change and Organizational Learning.

ERIC Educational Resources Information Center

Sumner, Mary

1985-01-01

A study was conducted to identify stage characteristics in terms of technology, applications, the role and responsibilities of the office automation organization, and planning and control strategies; and to describe the respective roles of data processing professionals, office automation analysts, and users in office automation systems development…

Grasp planning under uncertainty

NASA Technical Reports Server (NTRS)

Erkmen, A. M.; Stephanou, H. E.

1989-01-01

The planning of dexterous grasps for multifingered robot hands operating in uncertain environments is covered. A sensor-based approach to the planning of a reach path prior to grasping is first described. An on-line, joint space finger path planning algorithm for the enclose phase of grasping was then developed. The algorithm minimizes the impact momentum of the hand. It uses a Preshape Jacobian matrix to map task-level hand preshape requirements into kinematic constraints. A master slave scheme avoids inter-finger collisions and reduces the dimensionality of the planning problem.

Simulating Mission Command for Planning and Analysis

DTIC Science & Technology

2015-06-01

mission plan. 14. SUBJECT TERMS Mission Planning, CPM , PERT, Simulation, DES, Simkit, Triangle Distribution, Critical Path 15. NUMBER OF...Battalion Task Force CO Company CPM Critical Path Method DES Discrete Event Simulation FA BAT Field Artillery Battalion FEL Future Event List FIST...management tools that can be utilized to find the critical path in military projects. These are the Critical Path Method ( CPM ) and the Program Evaluation and

Opportunities for Automation of Student Aid Processing in Postsecondary Institutions.

ERIC Educational Resources Information Center

St. John, Edward P.

1986-01-01

An overview of the options and opportunities postsecondary institutions should consider when developing plans for student aid automation is provided. The role of automation in the financial aid office, interfaces with institutional and external systems, alternative approaches to automation, and the need for an institutional strategy for automation…

Developing an automated speech-recognition telephone diabetes intervention.

PubMed

Goldman, Roberta E; Sanchez-Hernandez, Maya; Ross-Degnan, Dennis; Piette, John D; Trinacty, Connie Mah; Simon, Steven R

2008-08-01

Many patients do not receive guideline-recommended care for diabetes and other chronic conditions. Automated speech-recognition telephone outreach to supplement in-person physician-patient communication may enhance patient care for chronic illness. We conducted this study to inform the development of an automated telephone outreach intervention for improving diabetes care among members of a large, not-for-profit health plan. In-depth telephone interviews with qualitative analysis. participants Individuals with diabetes (n=36) enrolled in a large regional health plan in the USA. Main outcome measure Patients' opinions about automated speech-recognition telephone technology. Patients who were recently diagnosed with diabetes and some with diabetes for a decade or more expressed basic informational needs. While most would prefer to speak with a live person rather than a computer-recorded voice, many felt that the automated system could successfully supplement the information they receive from their physicians and could serve as an integral part of their care. Patients suggested that such a system could provide specific dietary advice, information about diabetes and its self-care, a call-in menu of information topics, reminders about laboratory test results and appointments, tracking of personal laboratory results and feedback about their self-monitoring. While some patients expressed negative attitudes toward automated speech recognition telephone systems generally, most felt that a variety of functions of such a system could be beneficial to their diabetes care. In-depth interviews resulted in substantive input from health plan members for the design of an automated telephone outreach system to supplement in-person physician-patient communication in this population.

Failure mode and effect analysis oriented to risk-reduction interventions in intraoperative electron radiation therapy: the specific impact of patient transportation, automation, and treatment planning availability.

PubMed

López-Tarjuelo, Juan; Bouché-Babiloni, Ana; Santos-Serra, Agustín; Morillo-Macías, Virginia; Calvo, Felipe A; Kubyshin, Yuri; Ferrer-Albiach, Carlos

2014-11-01

Industrial companies use failure mode and effect analysis (FMEA) to improve quality. Our objective was to describe an FMEA and subsequent interventions for an automated intraoperative electron radiotherapy (IOERT) procedure with computed tomography simulation, pre-planning, and a fixed conventional linear accelerator. A process map, an FMEA, and a fault tree analysis are reported. The equipment considered was the radiance treatment planning system (TPS), the Elekta Precise linac, and TN-502RDM-H metal-oxide-semiconductor-field-effect transistor in vivo dosimeters. Computerized order-entry and treatment-automation were also analyzed. Fifty-seven potential modes and effects were identified and classified into 'treatment cancellation' and 'delivering an unintended dose'. They were graded from 'inconvenience' or 'suboptimal treatment' to 'total cancellation' or 'potentially wrong' or 'very wrong administered dose', although these latter effects were never experienced. Risk priority numbers (RPNs) ranged from 3 to 324 and totaled 4804. After interventions such as double checking, interlocking, automation, and structural changes the final total RPN was reduced to 1320. FMEA is crucial for prioritizing risk-reduction interventions. In a semi-surgical procedure like IOERT double checking has the potential to reduce risk and improve quality. Interlocks and automation should also be implemented to increase the safety of the procedure. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Pedestrian flow-path modeling to support tsunami evacuation and disaster relief planning in the U.S. Pacific Northwest

USGS Publications Warehouse

Wood, Nathan J.; Jones, Jeanne M.; Schmidtlein, Mathew; Schelling, John; Frazier, T.

2016-01-01

Successful evacuations are critical to saving lives from future tsunamis. Pedestrian-evacuation modeling related to tsunami hazards primarily has focused on identifying areas and the number of people in these areas where successful evacuations are unlikely. Less attention has been paid to identifying evacuation pathways and population demand at assembly areas for at-risk individuals that may have sufficient time to evacuate. We use the neighboring coastal communities of Hoquiam, Aberdeen, and Cosmopolis (Washington, USA) and the local tsunami threat posed by Cascadia subduction zone earthquakes as a case study to explore the use of geospatial, least-cost-distance evacuation modeling for supporting evacuation outreach, response, and relief planning. We demonstrate an approach that uses geospatial evacuation modeling to (a) map the minimum pedestrian travel speeds to safety, the most efficient paths, and collective evacuation basins, (b) estimate the total number and demographic description of evacuees at predetermined assembly areas, and (c) determine which paths may be compromised due to earthquake-induced ground failure. Results suggest a wide range in the magnitude and type of evacuees at predetermined assembly areas and highlight parts of the communities with no readily accessible assembly area. Earthquake-induced ground failures could obstruct access to some assembly areas, cause evacuees to reroute to get to other assembly areas, and isolate some evacuees from relief personnel. Evacuation-modeling methods and results discussed here have implications and application to tsunami-evacuation outreach, training, response procedures, mitigation, and long-term land use planning to increase community resilience.

System cost performance analysis (study 2.3). Volume 1: Executive summary. [unmanned automated payload programs and program planning

NASA Technical Reports Server (NTRS)

Campbell, B. H.

1974-01-01

A study is described which was initiated to identify and quantify the interrelationships between and within the performance, safety, cost, and schedule parameters for unmanned, automated payload programs. The result of the investigation was a systems cost/performance model which was implemented as a digital computer program and could be used to perform initial program planning, cost/performance tradeoffs, and sensitivity analyses for mission model and advanced payload studies. Program objectives and results are described briefly.

Maintenance of Automated Library Systems.

ERIC Educational Resources Information Center

Epstein, Susan Baerg

1983-01-01

Discussion of the maintenance of both the software and hardware in an automated library system highlights maintenance by the vendor, contracts and costs, the maintenance log, downtime, and planning for trouble. (EJS)

Adaptive Liver Stereotactic Body Radiation Therapy: Automated Daily Plan Reoptimization Prevents Dose Delivery Degradation Caused by Anatomy Deformations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leinders, Suzanne M.; Delft University of Technology, Delft; Breedveld, Sebastiaan

Purpose: To investigate how dose distributions for liver stereotactic body radiation therapy (SBRT) can be improved by using automated, daily plan reoptimization to account for anatomy deformations, compared with setup corrections only. Methods and Materials: For 12 tumors, 3 strategies for dose delivery were simulated. In the first strategy, computed tomography scans made before each treatment fraction were used only for patient repositioning before dose delivery for correction of detected tumor setup errors. In adaptive second and third strategies, in addition to the isocenter shift, intensity modulated radiation therapy beam profiles were reoptimized or both intensity profiles and beam orientationsmore » were reoptimized, respectively. All optimizations were performed with a recently published algorithm for automated, multicriteria optimization of both beam profiles and beam angles. Results: In 6 of 12 cases, violations of organs at risk (ie, heart, stomach, kidney) constraints of 1 to 6 Gy in single fractions occurred in cases of tumor repositioning only. By using the adaptive strategies, these could be avoided (<1 Gy). For 1 case, this needed adaptation by slightly underdosing the planning target volume. For 2 cases with restricted tumor dose in the planning phase to avoid organ-at-risk constraint violations, fraction doses could be increased by 1 and 2 Gy because of more favorable anatomy. Daily reoptimization of both beam profiles and beam angles (third strategy) performed slightly better than reoptimization of profiles only, but the latter required only a few minutes of computation time, whereas full reoptimization took several hours. Conclusions: This simulation study demonstrated that replanning based on daily acquired computed tomography scans can improve liver stereotactic body radiation therapy dose delivery.« less

Production planning, production systems for flexible automation

NASA Astrophysics Data System (ADS)

Spur, G.; Mertins, K.

1982-09-01

Trends in flexible manufacturing system (FMS) applications are reviewed. Machining systems contain machines which complement each other and can replace each other. Computer controlled storage systems are widespread, with central storage capacity ranging from 20 pallet spaces to 200 magazine spaces. Handling function is fulfilled by pallet chargers in over 75% of FMS's. Data system degree of automation varies considerably. No trends are noted for transport systems.

Automation - Changes in cognitive demands and mental workload

NASA Technical Reports Server (NTRS)

Tsang, Pamela S.; Johnson, Walter W.

1987-01-01

The effect of partial automation on mental workloads in man/machine tasks is investigated experimentally. Subjective workload measures are obtained from six subjects after performance of a task battery comprising two manual (flight-path control, FC, and target acquisition, TA) tasks and one decisionmaking (engine failure, EF) task; the FC task was performed in both a fully manual (altitude and lateral control) mode and in a semiautomated mode (autmatic latitude control). The performance results and subjective evaluations are presented in graphs and characterized in detail. The automation is shown to improve objective performance and lower subjective workload significantly in the combined FC/TA task, but not in the FC task alone or in the FC/EF task.

Small Libraries Online: Automating Circulation and Public Access Catalogs. Participant Workbook.

ERIC Educational Resources Information Center

Garcia, C. Rebecca; Bridge, Frank R.

This workbook, meant to be used in a workshop, presents information on and guidelines for automating small libraries: (1) planning for automation; (2) automated system procurement and evaluation; (3) data conversion issues; (4) sample configuration worksheets; (5) sample configuration costs; (6) site preparation; (7) training; and (8) acceptance…

Sequence-of-events-driven automation of the deep space network

NASA Technical Reports Server (NTRS)

Hill, R., Jr.; Fayyad, K.; Smyth, C.; Santos, T.; Chen, R.; Chien, S.; Bevan, R.

1996-01-01

In February 1995, sequence-of-events (SOE)-driven automation technology was demonstrated for a Voyager telemetry downlink track at DSS 13. This demonstration entailed automated generation of an operations procedure (in the form of a temporal dependency network) from project SOE information using artificial intelligence planning technology and automated execution of the temporal dependency network using the link monitor and control operator assistant system. This article describes the overall approach to SOE-driven automation that was demonstrated, identifies gaps in SOE definitions and project profiles that hamper automation, and provides detailed measurements of the knowledge engineering effort required for automation.

Sequence-of-Events-Driven Automation of the Deep Space Network

NASA Technical Reports Server (NTRS)

Hill, R., Jr.; Fayyad, K.; Smyth, C.; Santos, T.; Chen, R.; Chien, S.; Bevan, R.

1996-01-01

In February 1995, sequence-of-events (SOE)-driven automation technology was demonstrated for a Voyager telemetry downlink track at DSS 13. This demonstration entailed automated generation of an operations procedure (in the form of a temporal dependency network) from project SOE information using artificial intelligence planning technology and automated execution of the temporal dependency network using the link monitor and control operator assistant system. This article describes the overall approach to SOE-driven automation that was demonstrated, identifies gaps in SOE definitions and project profiles that hamper automation, and provides detailed measurements of the knowledge engineering effort required for automation.

A path planning method for robot end effector motion using the curvature theory of the ruled surfaces

NASA Astrophysics Data System (ADS)

Güler, Fatma; Kasap, Emin

Using the curvature theory for the ruled surfaces a technique for robot trajectory planning is presented. This technique ensures the calculation of robot’s next path. The positional variation of the Tool Center Point (TCP), linear velocity, angular velocity are required in the work area of the robot. In some circumstances, it may not be physically achievable and a re-computation of the robot trajectory might be necessary. This technique is suitable for re-computation of the robot trajectory. We obtain different robot trajectories which change depending on the darboux angle function and define trajectory ruled surface family with a common trajectory curve with the rotation trihedron. Also, the motion of robot end effector is illustrated with examples.

Selecting and Planning for an Automated Library System: Guidelines for Libraries.

ERIC Educational Resources Information Center

Piccininni, James

Guidelines are given for automating a library. Issues arising in automation are illustrated through the experience of the Doherty Library of the University of St. Thomas, Houston (Texas). The first step is to decide what type of system is right for the needs of the library and its patrons. In considering vendors of systems, it is important to…

[Automation in surgery: a systematical approach].

PubMed

Strauss, G; Meixensberger, J; Dietz, A; Manzey, D

2007-04-01

Surgical assistance systems permit a misalignment from the purely manual to an assisted activity of the surgeon (automation). Automation defines a system, that partly or totally fulfils function, those was carried out before totally or partly by the user. The organization of surgical assistance systems following application (planning, simulation, intraoperative navigation and visualization) or technical configuration of the system (manipulator, robot) is not suitable for a description of the interaction between user (surgeon) and the system. The available work has the goal of providing a classification for the degree of the automation of surgical interventions and describing by examples. The presented classification orients itself at pre-working from the Human-Factors-Sciences. As a condition for an automation of a surgical intervention applies that an assumption of a task, which was alone assigned so far to the surgeon takes place via the system. For both reference objects (humans and machine) the condition passively or actively comes into consideration. Besides can be classified according to which functions are taken over during a selected function division by humans and/or the surgical assistance system. Three functional areas were differentiated: "information acquisition and -analysis", "decision making and action planning" as well as "execution of the surgical action". From this results a classification of pre- and intraoperative surgical assist systems in six categories, which represent different automation degrees. The classification pattern is described and illustrated on the basis of surgical of examples.

Automated CPX support system preliminary design phase

NASA Technical Reports Server (NTRS)

Bordeaux, T. A.; Carson, E. T.; Hepburn, C. D.; Shinnick, F. M.

1984-01-01

The development of the Distributed Command and Control System (DCCS) is discussed. The development of an automated C2 system stimulated the development of an automated command post exercise (CPX) support system to provide a more realistic stimulus to DCCS than could be achieved with the existing manual system. An automated CPX system to support corps-level exercise was designed. The effort comprised four tasks: (1) collecting and documenting user requirements; (2) developing a preliminary system design; (3) defining a program plan; and (4) evaluating the suitability of the TRASANA FOURCE computer model.

Calibration of neural networks using genetic algorithms, with application to optimal path planning

NASA Technical Reports Server (NTRS)

Smith, Terence R.; Pitney, Gilbert A.; Greenwood, Daniel

1987-01-01

Genetic algorithms (GA) are used to search the synaptic weight space of artificial neural systems (ANS) for weight vectors that optimize some network performance function. GAs do not suffer from some of the architectural constraints involved with other techniques and it is straightforward to incorporate terms into the performance function concerning the metastructure of the ANS. Hence GAs offer a remarkably general approach to calibrating ANS. GAs are applied to the problem of calibrating an ANS that finds optimal paths over a given surface. This problem involves training an ANS on a relatively small set of paths and then examining whether the calibrated ANS is able to find good paths between arbitrary start and end points on the surface.

Contrast enhanced computed tomography and reconstruction of hepatic vascular system for transjugular intrahepatic portal systemic shunt puncture path planning.

PubMed

Qin, Jian-Ping; Tang, Shan-Hong; Jiang, Ming-De; He, Qian-Wen; Chen, Hong-Bin; Yao, Xin; Zeng, Wei-Zheng; Gu, Ming

2015-08-28

To describe a method for the transjugular intrahepatic portal systemic shunt (TIPS) placement performed with the aid of contrast-enhanced computed tomography (CECT) and three-dimensional reconstructed vascular images (3D RVIs), and to assess its safety and effectiveness. Four hundred and ninety patients were treated with TIPS between January 2005 and December 2012. All patients underwent liver CECT and reconstruction of 3D RVIs of the right hepatic vein to portal vein (PV) prior to the operation. The 3D RVIs were carefully reviewed to plan the puncture path from the start to target points for needle pass through the PV in the TIPS procedure. The improved TIPS procedure was successful in 483 (98.6%) of the 490 patients. The number of punctures attempted was one in 294 (60%) patients, 2 to 3 in 147 (30%) patients, 4 to 6 in 25 (5.1%) patients and more than 6 in 17 (3.5%) patients. Seven patients failed. Of the 490 patients, 12 had punctures into the artery, 15 into the bile duct, eight into the gallbladder, and 18 through the liver capsule. Analysis of the portograms from the 483 successful cases indicated that the puncture points were all located distally to the PV bifurcation on anteroposterior images, while the points were located proximally to the bifurcation in the three cases with intraabdominal bleeding. The complications included three cases of bleeding, of whom one died and two needed surgery. Use of CECT and 3D RVIs to plan the puncture path for TIPS procedure is safe, simple and effective for clinical use.

The planning and implementation of a demand-side management/distribution automation system at Taiwan Power Company

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, S.S.; Chen, Yun-Wu

1994-12-31

This paper would describe the Taipower`s experience of DSM/DAS development. For the past 5 years, the demand of electricity has maintained a high annual growth rate of 8.45% due to economic prosperity in Taiwan. As the environmental protection consciousness has recently made Taipower difficult to develope and construct new power plants, substations, transmission and distribution lines, and our power grid is an independent system, we do need to concern how to do DSM to manage the load problems. Since 1984, Taipower has established two pilot systems and these systems performed the functions of fault detect and isolation certainly good formore » Distribution Automation. With the rapid development of computer, communication and control technology, the concept of the DAS has gradually been implemented in real cases. Taipower organized an engineering task group to study DAS several years ago, and based on the operation experience of the existing systems, today Taipower is planning to launch a new DAS project for Tai-Chung area. According to Taipower requirements, the DAS will have the functions of feeder automation, automatic meter reading, load management and disteibution system analysis.« less

Impact of automation: Measurement of performance, workload and behaviour in a complex control environment.

PubMed

Balfe, Nora; Sharples, Sarah; Wilson, John R

2015-03-01

This paper describes an experiment that was undertaken to compare three levels of automation in rail signalling; a high level in which an automated agent set routes for trains using timetable information, a medium level in which trains were routed along pre-defined paths, and a low level where the operator (signaller) was responsible for the movement of all trains. These levels are described in terms of a Rail Automation Model based on previous automation theory (Parasuraman et al., 2000). Performance, subjective workload, and signaller activity were measured for each level of automation running under both normal operating conditions and abnormal, or disrupted, conditions. The results indicate that perceived workload, during both normal and disrupted phases of the experiment, decreased as the level of automation increased and performance was most consistent (i.e. showed the least variation between participants) with the highest level of automation. The results give a strong case in favour of automation, particularly in terms of demonstrating the potential for automation to reduce workload, but also suggest much benefit can achieved from a mid-level of automation potentially at a lower cost and complexity. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Administrative automation in a scientific environment

NASA Technical Reports Server (NTRS)

Jarrett, J. R.

1984-01-01

Although the scientific personnel at GSFC were advanced in the development and use of hardware and software for scientific applications, resistance to the use of automation or purchase of terminals, software and services, specifically for administrative functions was widespread. The approach used to address problems and constraints and plans for administrative automation within the Space and Earth Sciences Directorate are delineated. Accomplishments thus far include reduction of paperwork and manual efforts; improved communications through telemail and committees; additional support staff; increased awareness at all levels on ergonomic concerns and the need for training; better equipment; improved ADP skills through experience; management commitment; and an overall strategy for automating.

Power subsystem automation study

NASA Technical Reports Server (NTRS)

Imamura, M. S.; Moser, R. L.; Veatch, M.

1983-01-01

Generic power-system elements and their potential faults are identified. Automation functions and their resulting benefits are defined and automation functions between power subsystem, central spacecraft computer, and ground flight-support personnel are partitioned. All automation activities were categorized as data handling, monitoring, routine control, fault handling, planning and operations, or anomaly handling. Incorporation of all these classes of tasks, except for anomaly handling, in power subsystem hardware and software was concluded to be mandatory to meet the design and operational requirements of the space station. The key drivers are long mission lifetime, modular growth, high-performance flexibility, a need to accommodate different electrical user-load equipment, onorbit assembly/maintenance/servicing, and potentially large number of power subsystem components. A significant effort in algorithm development and validation is essential in meeting the 1987 technology readiness date for the space station.

46 CFR 62.20-3 - Plans for information.

Code of Federal Regulations, 2010 CFR

2010-10-01

...-based system hardware. (3) Safety controls. (4) Automated electric power management. (5) Automation... COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING VITAL SYSTEM AUTOMATION Plan... Officer in Charge, Marine Inspection, for use in the evaluation of automated systems provided to replace...

The application of automated operations at the Institutional Processing Center

NASA Technical Reports Server (NTRS)

Barr, Thomas H.

1993-01-01

The JPL Institutional and Mission Computing Division, Communications, Computing and Network Services Section, with its mission contractor, OAO Corporation, have for some time been applying automation to the operation of JPL's Information Processing Center (IPC). Automation does not come in one easy to use package. Automation for a data processing center is made up of many different software and hardware products supported by trained personnel. The IPC automation effort formally began with console automation, and has since spiraled out to include production scheduling, data entry, report distribution, online reporting, failure reporting and resolution, documentation, library storage, and operator and user education, while requiring the interaction of multi-vendor and locally developed software. To begin the process, automation goals are determined. Then a team including operations personnel is formed to research and evaluate available options. By acquiring knowledge of current products and those in development, taking an active role in industry organizations, and learning of other data center's experiences, a forecast can be developed as to what direction technology is moving. With IPC management's approval, an implementation plan is developed and resources identified to test or implement new systems. As an example, IPC's new automated data entry system was researched by Data Entry, Production Control, and Advance Planning personnel. A proposal was then submitted to management for review. A determination to implement the new system was made and elements/personnel involved with the initial planning performed the implementation. The final steps of the implementation were educating data entry personnel in the areas effected and procedural changes necessary to the successful operation of the new system.

Conceptual design of an aircraft automated coating removal system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, J.E.; Draper, J.V.; Pin, F.G.

1996-05-01

Paint stripping of the U.S. Air Force`s large transport aircrafts is currently a labor-intensive, manual process. Significant reductions in costs, personnel and turnaround time can be accomplished by the judicious use of automation in some process tasks. This paper presents the conceptual design of a coating removal systems for the tail surfaces of the C-5 plane. Emphasis is placed on the technology selection to optimize human-automation synergy with respect to overall costs, throughput, quality, safety, and reliability. Trade- offs between field-proven vs. research-requiring technologies, and between expected gain vs. cost and complexity, have led to a conceptual design which ismore » semi-autonomous (relying on the human for task specification and disturbance handling) yet incorporates sensor- based automation (for sweep path generation and tracking, surface following, stripping quality control and tape/breach handling).« less

Explore the Many Paths to Leadership

ERIC Educational Resources Information Center

Crow, Tracy

2015-01-01

The road to leadership is not necessarily one that educators plan carefully with a series of logical steps. Certainly some educators start as teachers and then systematically work through a traditional hierarchy on their way to the superintendency. No matter their role or their path, education leaders demand more from themselves and others and…

Dosimetric benefits of automation in the treatment of lower thoracic esophageal cancer: Is manual planning still an alternative option?

PubMed

Li, Xiadong; Wang, Lu; Wang, Jiahao; Han, Xu; Xia, Bing; Wu, Shixiu; Hu, Weigang

2017-01-01

This study aimed to design automated volumetric-modulated arc therapy (VMAT) plans in Pinnacle auto-planning and compare it with manual plans for patients with lower thoracic esophageal cancer (EC). Thirty patients with lower thoracic EC were randomly selected for replanning VMAT plans using auto-planning in Pinnacle treatment planning system (TPS) version 9.10. Historical plans of these patients were then compared. Dose-volume histogram (DVH) statistics, dose uniformity, and dose homogeneity were analyzed to evaluate treatment plans. Auto-planning was superior in terms of conformity index (CI) and homogeneity index (HI) for planning target volume (PTV), significantly improving 8.2% (p = 0.013) and 25% (p = 0.007) compared with manual planning, respectively, and decreasing dose of heart and liver irradiated by 20 to 40 Gy and 5 to 30 Gy, respectively (p < 0.05). Meanwhile, auto-planning further reduced the maximum dose (D max ) of spinal cord by 6.9 Gy compared with manual planning (p = 0.000). Additionally, manual planning showed the significantly lower low-dose volume (V 5 ) for the lung (p = 0.005). For auto-planning, the V 5 of the lung was significantly associated with the relative volume index (the volume ratio of PTV to the lung), and the correlation coefficient (R) and p-value were 0.994 and 0.000. Pinnacle auto-planning achieved superior target conformity and homogeneity and similar target coverage compared with historical manual planning. Most of organs at risk (OARs) sparing was significantly improved by auto-planning except for the V 5 of the lung, and the low dose distribution was highly associated with PTV volume and lung volume in auto-planning. Copyright © 2017 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

Proposal for automated transformations on single-photon multipath qudits

NASA Astrophysics Data System (ADS)

Baldijão, R. D.; Borges, G. F.; Marques, B.; Solís-Prosser, M. A.; Neves, L.; Pádua, S.

2017-09-01

We propose a method for implementing automated state transformations on single-photon multipath qudits encoded in a one-dimensional transverse spatial domain. It relies on transferring the encoding from this domain to the orthogonal one by applying a spatial phase modulation with diffraction gratings, merging all the initial propagation paths by using a stable interferometric network, and filtering out the unwanted diffraction orders. The automation feature is attained by utilizing a programmable phase-only spatial light modulator (SLM) where properly designed diffraction gratings displayed on its screen will implement the desired transformations, including, among others, projections, permutations, and random operations. We discuss the losses in the process which is, in general, inherently nonunitary. Some examples of transformations are presented and, considering a realistic scenario, we analyze how they will be affected by the pixelated structure of the SLM screen. The method proposed here enables one to implement much more general transformations on multipath qudits than is possible with a SLM alone operating in the diagonal basis of which-path states. Therefore, it will extend the range of applicability for this encoding in high-dimensional quantum information and computing protocols as well as fundamental studies in quantum theory.

An automatic alignment system for measuring optical path of transmissometer based on light beam scanning

NASA Astrophysics Data System (ADS)

Zhou, Shudao; Ma, Zhongliang; Wang, Min; Peng, Shuling

2018-05-01

This paper proposes a novel alignment system based on the measurement of optical path using a light beam scanning mode in a transmissometer. The system controls both the probe beam and the receiving field of view while scanning in two vertical directions. The system then calculates the azimuth angle of the transmitter and the receiver to determine the precise alignment of the optical path. Experiments show that this method can determine the alignment angles in less than 10 min with errors smaller than 66 μrad in the azimuth. This system also features high collimation precision, process automation and simple installation.

Path Flow Estimation Using Time Varying Coefficient State Space Model

NASA Astrophysics Data System (ADS)

Jou, Yow-Jen; Lan, Chien-Lun

2009-08-01

The dynamic path flow information is very crucial in the field of transportation operation and management, i.e., dynamic traffic assignment, scheduling plan, and signal timing. Time-dependent path information, which is important in many aspects, is nearly impossible to be obtained. Consequently, researchers have been seeking estimation methods for deriving valuable path flow information from less expensive traffic data, primarily link traffic counts of surveillance systems. This investigation considers a path flow estimation problem involving the time varying coefficient state space model, Gibbs sampler, and Kalman filter. Numerical examples with part of a real network of the Taipei Mass Rapid Transit with real O-D matrices is demonstrated to address the accuracy of proposed model. Results of this study show that this time-varying coefficient state space model is very effective in the estimation of path flow compared to time-invariant model.

Dynamic Modeling and Soil Mechanics for Path Planning of the Mars Exploration Rovers

NASA Technical Reports Server (NTRS)

Trease, Brian; Arvidson, Raymond; Lindemann, Randel; Bennett, Keith; Zhou, Feng; Iagnemma, Karl; Senatore, Carmine; Van Dyke, Lauren

2011-01-01

To help minimize risk of high sinkage and slippage during drives and to better understand soil properties and rover terramechanics from drive data, a multidisciplinary team was formed under the Mars Exploration Rover (MER) project to develop and utilize dynamic computer-based models for rover drives over realistic terrains. The resulting tool, named ARTEMIS (Adams-based Rover Terramechanics and Mobility Interaction Simulator), consists of the dynamic model, a library of terramechanics subroutines, and the high-resolution digital elevation maps of the Mars surface. A 200-element model of the rovers was developed and validated for drop tests before launch, using MSC-Adams dynamic modeling software. Newly modeled terrain-rover interactions include the rut-formation effect of deformable soils, using the classical Bekker-Wong implementation of compaction resistances and bull-dozing effects. The paper presents the details and implementation of the model with two case studies based on actual MER telemetry data. In its final form, ARTEMIS will be used in a predictive manner to assess terrain navigability and will become part of the overall effort in path planning and navigation for both Martian and lunar rovers.

Cassini Tour Atlas Automated Generation

NASA Technical Reports Server (NTRS)

Grazier, Kevin R.; Roumeliotis, Chris; Lange, Robert D.

2011-01-01

During the Cassini spacecraft s cruise phase and nominal mission, the Cassini Science Planning Team developed and maintained an online database of geometric and timing information called the Cassini Tour Atlas. The Tour Atlas consisted of several hundreds of megabytes of EVENTS mission planning software outputs, tables, plots, and images used by mission scientists for observation planning. Each time the nominal mission trajectory was altered or tweaked, a new Tour Atlas had to be regenerated manually. In the early phases of Cassini s Equinox Mission planning, an a priori estimate suggested that mission tour designers would develop approximately 30 candidate tours within a short period of time. So that Cassini scientists could properly analyze the science opportunities in each candidate tour quickly and thoroughly so that the optimal series of orbits for science return could be selected, a separate Tour Atlas was required for each trajectory. The task of manually generating the number of trajectory analyses in the allotted time would have been impossible, so the entire task was automated using code written in five different programming languages. This software automates the generation of the Cassini Tour Atlas database. It performs with one UNIX command what previously took a day or two of human labor.

Planning for Library Automation in the United States.

ERIC Educational Resources Information Center

Culbertson, Don S.

The 15-year history of the development of library automation is traced, and four major obstacles which had to be overcome are identified: the lack of funds for development, programing, and testing; the need for a common data base; the need for cooperative arrangements among institutions; and the need for widely-available on-line processing. Seven…

Enroute flight planning: Evaluating design concepts for the development of cooperative problem-solving systems

NASA Technical Reports Server (NTRS)

Smith, Philip J.

1995-01-01

There are many problem-solving tasks that are too complex to fully automate given the current state of technology. Nevertheless, significant improvements in overall system performance could result from the introduction of well-designed computer aids. We have been studying the development of cognitive tools for one such problem-solving task, enroute flight path planning for commercial airlines. Our goal has been two-fold. First, we have been developing specific system designs to help with this important practical problem. Second, we have been using this context to explore general design concepts to guide in the development of cooperative problem-solving systems. These design concepts are described below, along with illustrations of their application.

Development Status: Automation Advanced Development Space Station Freedom Electric Power System

NASA Technical Reports Server (NTRS)

Dolce, James L.; Kish, James A.; Mellor, Pamela A.

1990-01-01

Electric power system automation for Space Station Freedom is intended to operate in a loop. Data from the power system is used for diagnosis and security analysis to generate Operations Management System (OMS) requests, which are sent to an arbiter, which sends a plan to a commander generator connected to the electric power system. This viewgraph presentation profiles automation software for diagnosis, scheduling, and constraint interfaces, and simulation to support automation development. The automation development process is diagrammed, and the process of creating Ada and ART versions of the automation software is described.

Hard paths, soft paths or no paths? Cross-cultural perceptions of water solutions

NASA Astrophysics Data System (ADS)

Wutich, A.; White, A. C.; White, D. D.; Larson, K. L.; Brewis, A.; Roberts, C.

2014-01-01

In this study, we examine how development status and water scarcity shape people's perceptions of "hard path" and "soft path" water solutions. Based on ethnographic research conducted in four semi-rural/peri-urban sites (in Bolivia, Fiji, New Zealand, and the US), we use content analysis to conduct statistical and thematic comparisons of interview data. Our results indicate clear differences associated with development status and, to a lesser extent, water scarcity. People in the two less developed sites were more likely to suggest hard path solutions, less likely to suggest soft path solutions, and more likely to see no path to solutions than people in the more developed sites. Thematically, people in the two less developed sites envisioned solutions that involve small-scale water infrastructure and decentralized, community-based solutions, while people in the more developed sites envisioned solutions that involve large-scale infrastructure and centralized, regulatory water solutions. People in the two water-scarce sites were less likely to suggest soft path solutions and more likely to see no path to solutions (but no more likely to suggest hard path solutions) than people in the water-rich sites. Thematically, people in the two water-rich sites seemed to perceive a wider array of unrealized potential soft path solutions than those in the water-scarce sites. On balance, our findings are encouraging in that they indicate that people are receptive to soft path solutions in a range of sites, even those with limited financial or water resources. Our research points to the need for more studies that investigate the social feasibility of soft path water solutions, particularly in sites with significant financial and natural resource constraints.

Hard paths, soft paths or no paths? Cross-cultural perceptions of water solutions

NASA Astrophysics Data System (ADS)

Wutich, A.; White, A. C.; Roberts, C. M.; White, D. D.; Larson, K. L.; Brewis, A.

2013-06-01

In this study, we examine how development status and water scarcity shape people's perceptions of "hard path" and "soft path" water solutions. Based on ethnographic research conducted in four semi-rural/peri-urban sites (in Bolivia, Fiji, New Zealand, and the US), we use content analysis to conduct statistical and thematic comparisons of interview data. Our results indicate clear differences based on development status and, to a lesser extent, water scarcity. People in less developed sites were more likely to suggest hard path solutions, less likely to suggest soft path solutions, and more likely to see no path to solutions than people in more developed sites. Thematically, people in less developed sites envisioned solutions that involve small-scale water infrastructure and decentralized, community based solutions, while people in more developed sites envisioned solutions that involve large-scale infrastructure and centralized, regulatory water solutions. People in water-scarce sites were less likely to suggest soft path solutions and more likely to see no path to solutions (but no more likely to suggest hard path solutions) than people in water-rich sites. Thematically, people in water-rich sites seemed to perceive a wider array of unrealized potential soft path solutions than those in water-scarce sites. On balance, our findings are encouraging in that they indicate that people are receptive to soft path solutions in a range of sites, even those with limited financial or water resources. Our research points to the need for more studies that investigate the social feasibility of soft path water solutions, particularly in sites with significant financial and natural resource constraints.

Automated power management and control

NASA Technical Reports Server (NTRS)

Dolce, James L.

1991-01-01

A comprehensive automation design is being developed for Space Station Freedom's electric power system. A joint effort between NASA's Office of Aeronautics and Exploration Technology and NASA's Office of Space Station Freedom, it strives to increase station productivity by applying expert systems and conventional algorithms to automate power system operation. The initial station operation will use ground-based dispatches to perform the necessary command and control tasks. These tasks constitute planning and decision-making activities that strive to eliminate unplanned outages. We perceive an opportunity to help these dispatchers make fast and consistent on-line decisions by automating three key tasks: failure detection and diagnosis, resource scheduling, and security analysis. Expert systems will be used for the diagnostics and for the security analysis; conventional algorithms will be used for the resource scheduling.

Computer Programs For Automated Welding System

NASA Technical Reports Server (NTRS)

Agapakis, John E.

1993-01-01

Computer programs developed for use in controlling automated welding system described in MFS-28578. Together with control computer, computer input and output devices and control sensors and actuators, provide flexible capability for planning and implementation of schemes for automated welding of specific workpieces. Developed according to macro- and task-level programming schemes, which increases productivity and consistency by reducing amount of "teaching" of system by technician. System provides for three-dimensional mathematical modeling of workpieces, work cells, robots, and positioners.

Automated fuel pin loading system

DOEpatents

Christiansen, David W.; Brown, William F.; Steffen, Jim M.

1985-01-01

An automated loading system for nuclear reactor fuel elements utilizes a gravity feed conveyor which permits individual fuel pins to roll along a constrained path perpendicular to their respective lengths. The individual lengths of fuel cladding are directed onto movable transports, where they are aligned coaxially with the axes of associated handling equipment at appropriate production stations. Each fuel pin can be reciprocated axially and/or rotated about its axis as required during handling steps. The fuel pins are inserted as a batch prior to welding of end caps by one of two disclosed welding systems.

Automated fuel pin loading system

DOEpatents

Christiansen, D.W.; Brown, W.F.; Steffen, J.M.

An automated loading system for nuclear reactor fuel elements utilizes a gravity feed conveyor which permits individual fuel pins to roll along a constrained path perpendicular to their respective lengths. The individual lengths of fuel cladding are directed onto movable transports, where they are aligned coaxially with the axes of associated handling equipment at appropriate production stations. Each fuel pin can be be reciprocated axially and/or rotated about its axis as required during handling steps. The fuel pins are inerted as a batch prior to welding of end caps by one of two disclosed welding systems.

MGA trajectory planning with an ACO-inspired algorithm

NASA Astrophysics Data System (ADS)

Ceriotti, Matteo; Vasile, Massimiliano

2010-11-01

Given a set of celestial bodies, the problem of finding an optimal sequence of swing-bys, deep space manoeuvres (DSM) and transfer arcs connecting the elements of the set is combinatorial in nature. The number of possible paths grows exponentially with the number of celestial bodies. Therefore, the design of an optimal multiple gravity assist (MGA) trajectory is a NP-hard mixed combinatorial-continuous problem. Its automated solution would greatly improve the design of future space missions, allowing the assessment of a large number of alternative mission options in a short time. This work proposes to formulate the complete automated design of a multiple gravity assist trajectory as an autonomous planning and scheduling problem. The resulting scheduled plan will provide the optimal planetary sequence and a good estimation of the set of associated optimal trajectories. The trajectory model consists of a sequence of celestial bodies connected by two-dimensional transfer arcs containing one DSM. For each transfer arc, the position of the planet and the spacecraft, at the time of arrival, are matched by varying the pericentre of the preceding swing-by, or the magnitude of the launch excess velocity, for the first arc. For each departure date, this model generates a full tree of possible transfers from the departure to the destination planet. Each leaf of the tree represents a planetary encounter and a possible way to reach that planet. An algorithm inspired by ant colony optimization (ACO) is devised to explore the space of possible plans. The ants explore the tree from departure to destination adding one node at the time: every time an ant is at a node, a probability function is used to select a feasible direction. This approach to automatic trajectory planning is applied to the design of optimal transfers to Saturn and among the Galilean moons of Jupiter. Solutions are compared to those found through more traditional genetic-algorithm techniques.

Implementation of an Automated System.

ERIC Educational Resources Information Center

Epstein, Susan Baerg

1983-01-01

Discussion of care and planning given to the implementation of an automated library system highlights informing the staff in the early stages, project management, involvement of the entire staff, the control log, time and money, where and when to go online, and implementation consultants. (EJS)

Automated Monitoring of Pipeline Rights-of-Way

NASA Technical Reports Server (NTRS)

Frost, Chard Ritchie

2010-01-01

NASA Ames Research Center and the Pipeline Research Council International, Inc. have partnered in the formation of a research program to identify and develop the key technologies required to enable automated detection of threats to gas and oil transmission and distribution pipelines. This presentation describes the Right-of-way Automated Monitoring (RAM) program and highlights research successes to date, continuing challenges to implementing the RAM objectives, and the program's ongoing work and plans.

Hierarchical Motion Planning for Autonomous Aerial and Terrestrial Vehicles

NASA Astrophysics Data System (ADS)

Cowlagi, Raghvendra V.

Autonomous mobile robots---both aerial and terrestrial vehicles---have gained immense importance due to the broad spectrum of their potential military and civilian applications. One of the indispensable requirements for the autonomy of a mobile vehicle is the vehicle's capability of planning and executing its motion, that is, finding appropriate control inputs for the vehicle such that the resulting vehicle motion satisfies the requirements of the vehicular task. The motion planning and control problem is inherently complex because it involves two disparate sub-problems: (1) satisfaction of the vehicular task requirements, which requires tools from combinatorics and/or formal methods, and (2) design of the vehicle control laws, which requires tools from dynamical systems and control theory. Accordingly, this problem is usually decomposed and solved over two levels of hierarchy. The higher level, called the geometric path planning level, finds a geometric path that satisfies the vehicular task requirements, e.g., obstacle avoidance. The lower level, called the trajectory planning level, involves sufficient smoothening of this geometric path followed by a suitable time parametrization to obtain a reference trajectory for the vehicle. Although simple and efficient, such hierarchical decomposition suffers a serious drawback: the geometric path planner has no information of the kinematical and dynamical constraints of the vehicle. Consequently, the geometric planner may produce paths that the trajectory planner cannot transform into a feasible reference trajectory. Two main ideas appear in the literature to remedy this problem: (a) randomized sampling-based planning, which eliminates the geometric planner altogether by planning in the vehicle state space, and (b) geometric planning supported by feedback control laws. The former class of methods suffer from a lack of optimality of the resultant trajectory, while the latter class of methods makes a restrictive assumption

Automation of Cassini Support Imaging Uplink Command Development

NASA Technical Reports Server (NTRS)

Ly-Hollins, Lisa; Breneman, Herbert H.; Brooks, Robert

2010-01-01

"Support imaging" is imagery requested by other Cassini science teams to aid in the interpretation of their data. The generation of the spacecraft command sequences for these images is performed by the Cassini Instrument Operations Team. The process initially established for doing this was very labor-intensive, tedious and prone to human error. Team management recognized this process as one that could easily benefit from automation. Team members were tasked to document the existing manual process, develop a plan and strategy to automate the process, implement the plan and strategy, test and validate the new automated process, and deliver the new software tools and documentation to Flight Operations for use during the Cassini extended mission. In addition to the goals of higher efficiency and lower risk in the processing of support imaging requests, an effort was made to maximize adaptability of the process to accommodate uplink procedure changes and the potential addition of new capabilities outside the scope of the initial effort.

SU-F-J-93: Automated Segmentation of High-Resolution 3D WholeBrain Spectroscopic MRI for Glioblastoma Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schreibmann, E; Shu, H; Cordova, J

Purpose: We report on an automated segmentation algorithm for defining radiation therapy target volumes using spectroscopic MR images (sMRI) acquired at nominal voxel resolution of 100 microliters. Methods: Wholebrain sMRI combining 3D echo-planar spectroscopic imaging, generalized auto-calibrating partially-parallel acquisitions, and elliptical k-space encoding were conducted on 3T MRI scanner with 32-channel head coil array creating images. Metabolite maps generated include choline (Cho), creatine (Cr), and N-acetylaspartate (NAA), as well as Cho/NAA, Cho/Cr, and NAA/Cr ratio maps. Automated segmentation was achieved by concomitantly considering sMRI metabolite maps with standard contrast enhancing (CE) imaging in a pipeline that first uses the watermore » signal for skull stripping. Subsequently, an initial blob of tumor region is identified by searching for regions of FLAIR abnormalities that also display reduced NAA activity using a mean ratio correlation and morphological filters. These regions are used as starting point for a geodesic level-set refinement that adapts the initial blob to the fine details specific to each metabolite. Results: Accuracy of the segmentation model was tested on a cohort of 12 patients that had sMRI datasets acquired pre, mid and post-treatment, providing a broad range of enhancement patterns. Compared to classical imaging, where heterogeneity in the tumor appearance and shape across posed a greater challenge to the algorithm, sMRI’s regions of abnormal activity were easily detected in the sMRI metabolite maps when combining the detail available in the standard imaging with the local enhancement produced by the metabolites. Results can be imported in the treatment planning, leading in general increase in the target volumes (GTV60) when using sMRI+CE MRI compared to the standard CE MRI alone. Conclusion: Integration of automated segmentation of sMRI metabolite maps into planning is feasible and will likely streamline acceptance

Automated Scheduling of Science Activities for Titan Encounters by Cassini

NASA Technical Reports Server (NTRS)

Ray, Trina L.; Knight, Russel L.; Mohr, Dave

2014-01-01

In an effort to demonstrate the efficacy of automated planning and scheduling techniques for large missions, we have adapted ASPEN (Activity Scheduling and Planning Environment) [1] and CLASP (Compressed Large-scale Activity Scheduling and Planning) [2] to the domain of scheduling high-level science goals into conflict-free operations plans for Titan encounters by the Cassini spacecraft.

Establishment and discontinuance criteria for automated weather observing systems (AWOS)

DOT National Transportation Integrated Search

1983-05-01

This report develops establishment and discontinuance criteria for automated : weather observing systems (AWOS) for publication in FAA Order 703l.2B, Airway : Planning Standard Number One. Airway Planning Standard Number One contains : the policy and...

Library Automation in Sub Saharan Africa: Case Study of the University of Botswana

ERIC Educational Resources Information Center

Mutula, Stephen Mudogo

2012-01-01

Purpose: This article aims to present experiences and the lessons learned from the University of Botswana (UB) library automation project. The implications of the project for similar libraries planning automation in sub Saharan Africa and beyond are adduced. Design/methodology/approach: The article is a case study of library automation at the…

Optimized path planning for soft tissue resection via laser vaporization

NASA Astrophysics Data System (ADS)

Ross, Weston; Cornwell, Neil; Tucker, Matthew; Mann, Brian; Codd, Patrick

2018-02-01

Robotic and robotic-assisted surgeries are becoming more prevalent with the promise of improving surgical outcomes through increased precision, reduced operating times, and minimally invasive procedures. The handheld laser scalpel in neurosurgery has been shown to provide a more gentle approach to tissue manipulation on or near critical structures over classical tooling, though difficulties of control have prevented large scale adoption of the tool. This paper presents a novel approach to generating a cutting path for the volumetric resection of tissue using a computer-guided laser scalpel. A soft tissue ablation simulator is developed and used in conjunction with an optimization routine to select parameters which maximize the total resection of target tissue while minimizing the damage to surrounding tissue. The simulator predicts the ablative properties of tissue from an interrogation cut for tuning and simulates the removal of a tumorous tissue embedded on the surface of healthy tissue using a laser scalpel. We demonstrate the ability to control depth and smoothness of cut using genetic algorithms to optimize the ablation parameters and cutting path. The laser power level, cutting rate and spacing between cuts are optimized over multiple surface cuts to achieve the desired resection volumes.

SU-C-BRB-01: Automated Dose Deformation for Re-Irradiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lim, S; Kainz, K; Li, X

Purpose: An objective of retreatment planning is to minimize dose to previously irradiated tissues. Conventional retreatment planning is based largely on best-guess superposition of the previous treatment’s isodose lines. In this study, we report a rigorous, automated retreatment planning process to minimize dose to previously irradiated organs at risk (OAR). Methods: Data for representative patients previously treated using helical tomotherapy and later retreated in the vicinity of the original disease site were retrospectively analyzed in an automated fashion using a prototype treatment planning system equipped with a retreatment planning module (Accuray, Inc.). The initial plan’s CT, structures, and planned dosemore » were input along with the retreatment CT and structure set. Using a deformable registration algorithm implemented in the module, the initially planned dose and structures were warped onto the retreatment CT. An integrated third-party sourced software (MIM, Inc.) was used to evaluate registration quality and to contour overlapping regions between isodose lines and OARs, providing additional constraints during retreatment planning. The resulting plan and the conventionally generated retreatment plan were compared. Results: Jacobian maps showed good quality registration between the initial plan and retreatment CTs. For a right orbit case, the dose deformation facilitated delineating the regions of the eyes and optic chiasm originally receiving 13 to 42 Gy. Using these regions as dose constraints, the new retreatment plan resulted in V50 reduction of 28% for the right eye and 8% for the optic chiasm, relative to the conventional plan. Meanwhile, differences in the PTV dose coverage were clinically insignificant. Conclusion: Automated retreatment planning with dose deformation and definition of previously-irradiated regions allowed for additional planning constraints to be defined to minimize re-irradiation of OARs. For serial organs that do not

Probabilistic Reasoning for Robustness in Automated Planning

NASA Technical Reports Server (NTRS)

Schaffer, Steven; Clement, Bradley; Chien, Steve

2007-01-01

A general-purpose computer program for planning the actions of a spacecraft or other complex system has been augmented by incorporating a subprogram that reasons about uncertainties in such continuous variables as times taken to perform tasks and amounts of resources to be consumed. This subprogram computes parametric probability distributions for time and resource variables on the basis of user-supplied models of actions and resources that they consume. The current system accepts bounded Gaussian distributions over action duration and resource use. The distributions are then combined during planning to determine the net probability distribution of each resource at any time point. In addition to a full combinatoric approach, several approximations for arriving at these combined distributions are available, including maximum-likelihood and pessimistic algorithms. Each such probability distribution can then be integrated to obtain a probability that execution of the plan under consideration would violate any constraints on the resource. The key idea is to use these probabilities of conflict to score potential plans and drive a search toward planning low-risk actions. An output plan provides a balance between the user s specified averseness to risk and other measures of optimality.

A biomimetic, energy-harvesting, obstacle-avoiding, path-planning algorithm for UAVs

NASA Astrophysics Data System (ADS)

Gudmundsson, Snorri

This dissertation presents two new approaches to energy harvesting for Unmanned Aerial Vehicles (UAV). One method is based on the Potential Flow Method (PFM); the other method seeds a wind-field map based on updraft peak analysis and then applies a variant of the Bellman-Ford algorithm to find the minimum-cost path. Both methods are enhanced by taking into account the performance characteristics of the aircraft using advanced performance theory. The combined approach yields five possible trajectories from which the one with the minimum energy cost is selected. The dissertation concludes by using the developed theory and modeling tools to simulate the flight paths of two small Unmanned Aerial Vehicles (sUAV) in the 500 kg and 250 kg class. The results show that, in mountainous regions, substantial energy can be recovered, depending on topography and wind characteristics. For the examples presented, as much as 50% of the energy was recovered for a complex, multi-heading, multi-altitude, 170 km mission in an average wind speed of 9 m/s. The algorithms constitute a Generic Intelligent Control Algorithm (GICA) for autonomous unmanned aerial vehicles that enables an extraction of atmospheric energy while completing a mission trajectory. At the same time, the algorithm. automatically adjusts the flight path in order to avoid obstacles, in a fashion not unlike what one would expect from living organisms, such as birds and insects. This multi-disciplinary approach renders the approach biomimetic, i.e. it constitutes a synthetic system that “mimics the formation and function of biological mechanisms and processes.”.

Do-It-Yourself Critical Path Method.

ERIC Educational Resources Information Center

Morris, Edward P., Jr.

This report describes the critical path method (CPM), a system for planning and scheduling work to get the best time-cost combination for any particular job. With the use of diagrams, the report describes how CPM works on a step-by-step basis. CPM uses a network to show which parts of a job must be done and how they would eventually fit together…

Space station automation study. Volume 1: Executive summary. Autonomous systems and assembly

NASA Technical Reports Server (NTRS)

1984-01-01

The space station automation study (SSAS) was to develop informed technical guidance for NASA personnel in the use of autonomy and autonomous systems to implement space station functions. The initial step taken by NASA in organizing the SSAS was to form and convene a panel of recognized expert technologists in automation, space sciences and aerospace engineering to produce a space station automation plan.

Research on optimal path planning algorithm of task-oriented optical remote sensing satellites

NASA Astrophysics Data System (ADS)

Liu, Yunhe; Xu, Shengli; Liu, Fengjing; Yuan, Jingpeng

2015-08-01

GEO task-oriented optical remote sensing satellite, is very suitable for long-term continuous monitoring and quick access to imaging. With the development of high resolution optical payload technology and satellite attitude control technology, GEO optical remote sensing satellites will become an important developing trend for aerospace remote sensing satellite in the near future. In the paper, we focused on GEO optical remote sensing satellite plane array stare imaging characteristics and real-time leading mission of earth observation mode, targeted on satisfying needs of the user with the minimum cost of maneuver, and put forward the optimal path planning algorithm centered on transformation from geographic coordinate space to Field of plane, and finally reduced the burden of the control system. In this algorithm, bounded irregular closed area on the ground would be transformed based on coordinate transformation relations in to the reference plane for field of the satellite payload, and then using the branch and bound method to search for feasible solutions, cutting off the non-feasible solution in the solution space based on pruning strategy; and finally trimming some suboptimal feasible solutions based on the optimization index until a feasible solution for the global optimum. Simulation and visualization presentation software testing results verified the feasibility and effectiveness of the strategy.

Movement Path Tortuosity Predicts Compliance With Therapeutic Behavioral Prompts in Patients With Traumatic Brain Injury.

PubMed

Kearns, William D; Fozard, James L; Ray, Roger D; Scott, Steven; Jasiewicz, Jan M; Craighead, Jeffrey D; Pagano, Craig V

2016-01-01

Rehabilitation of patients with traumatic brain injury typically includes therapeutic prompts for keeping appointments and adhering to medication regimens. Level of cognitive impairment may significantly affect a traumatic brain injury victim's ability to benefit from text-based prompting. We tested the hypothesis that spatial disorientation as measured by movement path tortuosity during ambulation would be associated with poorer compliance with automated prompts by veterans actively being treated for traumatic brain injury. Clinical polytrauma center. Ten (1 female) veteran patients mean age = 35.4 (SD = 12.4) years. Small group correlational study without random assignment. Fractal Dimension, a measure of movement path tortuosity derived from a GPS logging device used to record casual outdoor ambulation at the start of the study. Compliance with smart home machine-generated therapeutic prompts received during rehabilitation at the James A. Haley Veterans Administration Hospital Polytrauma Transitional Rehabilitation Program. A patient was compliant with a prompt if they transited from where the prompt was presented to the prescribed destination (both within the Polytrauma Transitional Rehabilitation Program) within 30 minutes. Noncompliance was failure to appear at the destination within the allotted time. Fractal dimension was significantly inversely related to overall prompt compliance (r = -0.603, n = 10, P = .032; 1-tailed). The findings support the hypothesis that increased spatial disorientation adversely impacts compliance with automated prompts throughout therapy. The results are consistent with previous studies linking elevated path tortuosity to cognitive impairment and increased risk for falls in assisted living facility residents.

Guidelines for implementing automation in a hospital laboratory setting--part II.

PubMed

Rodriques, Sarina

2007-03-28

Laboratories entering into a discussion regarding automation of their facility have a number of key issues that need to be considered right away. What is the financial impact going to be? How do we know which processes we should automate and which ones we shouldn't? Which vendor is going to best align with the goals of our organization? Developing a thorough and robust plan at the start of the automation process is vital to the overall success of the project. It requires dedicated staff members who are willing to do the research, crunch the numbers, and present the data effectively. In Part II of this manuscript, issues such as cost analyses, business plans, and purchasing decisions are each covered thoroughly.

Four years experience in APMS star plate processing - Results and future plans. [Automated Proper Motion Study

NASA Technical Reports Server (NTRS)

Newcomb, J. S.

1975-01-01

The present paper describes an automated system for measuring stellar proper motions on the basis of information contained in photographic plates. In this system, the images on a star plate are digitized by a scanning microdensitometer using light from a He-Ne gas laser, and a special-purpose computer arranges the measurements in computer-compatible form on magnetic tape. The scanning and image-reconstruction processes are briefly outlined, and the image-evaluation techniques are discussed. It is shown that the present system has been especially successful in measuring the proper motions of low-luminosity stars, including 119 stars with less than 1/10,000 of the solar bolometric luminosity. Plans for measurements of high-density Milky Way star plates are noted.

Pilot opinions on high level flight deck automation issues: Toward the development of a design philosophy

NASA Technical Reports Server (NTRS)

Tenney, Yvette J.; Rogers, William H.; Pew, Richard W.

1995-01-01

There has been much concern in recent years about the rapid increase in automation on commercial flight decks. The survey was composed of three major sections. The first section asked pilots to rate different automation components that exist on the latest commercial aircraft regarding their obtrusiveness and the attention and effort required in using them. The second section addressed general 'automation philosophy' issues. The third section focused on issues related to levels and amount of automation. The results indicate that pilots of advanced aircraft like their automation, use it, and would welcome more automation. However, they also believe that automation has many disadvantages, especially fully autonomous automation. They want their automation to be simple and reliable and to produce predictable results. The biggest needs for higher levels of automation were in pre-flight, communication, systems management, and task management functions, planning as well as response tasks, and high workload situations. There is an irony and a challenge in the implications of these findings. On the one hand pilots would like new automation to be simple and reliable, but they need it to support the most complex part of the job--managing and planning tasks in high workload situations.

Virtual Planning, Control, and Machining for a Modular-Based Automated Factory Operation in an Augmented Reality Environment

PubMed Central

Pai, Yun Suen; Yap, Hwa Jen; Md Dawal, Siti Zawiah; Ramesh, S.; Phoon, Sin Ye

2016-01-01

This study presents a modular-based implementation of augmented reality to provide an immersive experience in learning or teaching the planning phase, control system, and machining parameters of a fully automated work cell. The architecture of the system consists of three code modules that can operate independently or combined to create a complete system that is able to guide engineers from the layout planning phase to the prototyping of the final product. The layout planning module determines the best possible arrangement in a layout for the placement of various machines, in this case a conveyor belt for transportation, a robot arm for pick-and-place operations, and a computer numerical control milling machine to generate the final prototype. The robotic arm module simulates the pick-and-place operation offline from the conveyor belt to a computer numerical control (CNC) machine utilising collision detection and inverse kinematics. Finally, the CNC module performs virtual machining based on the Uniform Space Decomposition method and axis aligned bounding box collision detection. The conducted case study revealed that given the situation, a semi-circle shaped arrangement is desirable, whereas the pick-and-place system and the final generated G-code produced the highest deviation of 3.83 mm and 5.8 mm respectively. PMID:27271840

Virtual Planning, Control, and Machining for a Modular-Based Automated Factory Operation in an Augmented Reality Environment.

PubMed

Pai, Yun Suen; Yap, Hwa Jen; Md Dawal, Siti Zawiah; Ramesh, S; Phoon, Sin Ye

2016-06-07

This study presents a modular-based implementation of augmented reality to provide an immersive experience in learning or teaching the planning phase, control system, and machining parameters of a fully automated work cell. The architecture of the system consists of three code modules that can operate independently or combined to create a complete system that is able to guide engineers from the layout planning phase to the prototyping of the final product. The layout planning module determines the best possible arrangement in a layout for the placement of various machines, in this case a conveyor belt for transportation, a robot arm for pick-and-place operations, and a computer numerical control milling machine to generate the final prototype. The robotic arm module simulates the pick-and-place operation offline from the conveyor belt to a computer numerical control (CNC) machine utilising collision detection and inverse kinematics. Finally, the CNC module performs virtual machining based on the Uniform Space Decomposition method and axis aligned bounding box collision detection. The conducted case study revealed that given the situation, a semi-circle shaped arrangement is desirable, whereas the pick-and-place system and the final generated G-code produced the highest deviation of 3.83 mm and 5.8 mm respectively.

Virtual Planning, Control, and Machining for a Modular-Based Automated Factory Operation in an Augmented Reality Environment

NASA Astrophysics Data System (ADS)

Pai, Yun Suen; Yap, Hwa Jen; Md Dawal, Siti Zawiah; Ramesh, S.; Phoon, Sin Ye

2016-06-01

This study presents a modular-based implementation of augmented reality to provide an immersive experience in learning or teaching the planning phase, control system, and machining parameters of a fully automated work cell. The architecture of the system consists of three code modules that can operate independently or combined to create a complete system that is able to guide engineers from the layout planning phase to the prototyping of the final product. The layout planning module determines the best possible arrangement in a layout for the placement of various machines, in this case a conveyor belt for transportation, a robot arm for pick-and-place operations, and a computer numerical control milling machine to generate the final prototype. The robotic arm module simulates the pick-and-place operation offline from the conveyor belt to a computer numerical control (CNC) machine utilising collision detection and inverse kinematics. Finally, the CNC module performs virtual machining based on the Uniform Space Decomposition method and axis aligned bounding box collision detection. The conducted case study revealed that given the situation, a semi-circle shaped arrangement is desirable, whereas the pick-and-place system and the final generated G-code produced the highest deviation of 3.83 mm and 5.8 mm respectively.

The flight planning - flight management connection

NASA Technical Reports Server (NTRS)

Sorensen, J. A.

1984-01-01

Airborne flight management systems are currently being implemented to minimize direct operating costs when flying over a fixed route between a given city pair. Inherent in the design of these systems is that the horizontal flight path and wind and temperature models be defined and input into the airborne computer before flight. The wind/temperature model and horizontal path are products of the flight planning process. Flight planning consists of generating 3-D reference trajectories through a forecast wind field subject to certain ATC and transport operator constraints. The interrelationships between flight management and flight planning are reviewed, and the steps taken during the flight planning process are summarized.

NASA's Flexible Path for the Human Exploration

NASA Technical Reports Server (NTRS)

Soeder, James F.

2016-01-01

The idea of human exploration of Mars has been a topic in science fiction for close to a century. For the past 50 years it has been a major thrust in NASAs space mission planning. Currently, NASA is pursuing a flexible development path with the final goal to have humans on Mars. To reach Mars, new hardware will have to be developed and many technology hurdles will have to be overcome. This presentation discusses Mars and its Moons; the flexible path currently being followed; the hardware under development to support exploration; and the technical and organizational challenges that must be overcome to realize the age old dream of humans traveling to Mars.

Methodology for Prototyping Increased Levels of Automation for Spacecraft Rendezvous Functions

NASA Technical Reports Server (NTRS)

Hart, Jeremy J.; Valasek, John

2007-01-01

The Crew Exploration Vehicle necessitates higher levels of automation than previous NASA vehicles, due to program requirements for automation, including Automated Rendezvous and Docking. Studies of spacecraft development often point to the locus of decision-making authority between humans and computers (i.e. automation) as a prime driver for cost, safety, and mission success. Therefore, a critical component in the Crew Exploration Vehicle development is the determination of the correct level of automation. To identify the appropriate levels of automation and autonomy to design into a human space flight vehicle, NASA has created the Function-specific Level of Autonomy and Automation Tool. This paper develops a methodology for prototyping increased levels of automation for spacecraft rendezvous functions. This methodology is used to evaluate the accuracy of the Function-specific Level of Autonomy and Automation Tool specified levels of automation, via prototyping. Spacecraft rendezvous planning tasks are selected and then prototyped in Matlab using Fuzzy Logic techniques and existing Space Shuttle rendezvous trajectory algorithms.

Harnessing Vehicle Automation for Public Mobility -- An Overview of Ongoing Efforts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Young, Stanley E.

This presentation takes a look at the efforts to harness automated vehicle technology for public transport. The European CityMobil2 is the leading demonstration project in which automated shuttles were, or are planned to be, demonstrated in several cities and regions. The presentation provides a brief overview of the demonstrations at Oristano, Italy (July 2014), LaRochelle, France (Dec 2014), Lausanne, Switzerland (Apr 2015), Vantaa, Finland (July 2015), and Trikala, Greece (Sept 2015). In addition to technology exposition, the objectives included generating a legal framework for operation in each location and gaging the reaction of the public to unmanned shuttles, both ofmore » which were successfully achieved. Several such demonstrations are planned throughout the world, including efforts in North America in conjunction with the GoMentum Station in California. These early demonstration with low-speed automated shuttles provide a glimpse of the possible with a fully automated fleet of driverless vehicle providing a public transit service.« less

Integrated flexible manufacturing program for manufacturing automation and rapid prototyping

NASA Technical Reports Server (NTRS)

Brooks, S. L.; Brown, C. W.; King, M. S.; Simons, W. R.; Zimmerman, J. J.

1993-01-01

The Kansas City Division of Allied Signal Inc., as part of the Integrated Flexible Manufacturing Program (IFMP), is developing an integrated manufacturing environment. Several systems are being developed to produce standards and automation tools for specific activities within the manufacturing environment. The Advanced Manufacturing Development System (AMDS) is concentrating on information standards (STEP) and product data transfer; the Expert Cut Planner system (XCUT) is concentrating on machining operation process planning standards and automation capabilities; the Advanced Numerical Control system (ANC) is concentrating on NC data preparation standards and NC data generation tools; the Inspection Planning and Programming Expert system (IPPEX) is concentrating on inspection process planning, coordinate measuring machine (CMM) inspection standards and CMM part program generation tools; and the Intelligent Scheduling and Planning System (ISAPS) is concentrating on planning and scheduling tools for a flexible manufacturing system environment. All of these projects are working together to address information exchange, standardization, and information sharing to support rapid prototyping in a Flexible Manufacturing System (FMS) environment.

Evaluation of an artificial intelligence guided inverse planning system: clinical case study.

PubMed

Yan, Hui; Yin, Fang-Fang; Willett, Christopher

2007-04-01

An artificial intelligence (AI) guided method for parameter adjustment of inverse planning was implemented on a commercial inverse treatment planning system. For evaluation purpose, four typical clinical cases were tested and the results from both plans achieved by automated and manual methods were compared. The procedure of parameter adjustment mainly consists of three major loops. Each loop is in charge of modifying parameters of one category, which is carried out by a specially customized fuzzy inference system. A physician prescribed multiple constraints for a selected volume were adopted to account for the tradeoff between prescription dose to the PTV and dose-volume constraints for critical organs. The searching process for an optimal parameter combination began with the first constraint, and proceeds to the next until a plan with acceptable dose was achieved. The initial setup of the plan parameters was the same for each case and was adjusted independently by both manual and automated methods. After the parameters of one category were updated, the intensity maps of all fields were re-optimized and the plan dose was subsequently re-calculated. When final plan arrived, the dose statistics were calculated from both plans and compared. For planned target volume (PTV), the dose for 95% volume is up to 10% higher in plans using the automated method than those using the manual method. For critical organs, an average decrease of the plan dose was achieved. However, the automated method cannot improve the plan dose for some critical organs due to limitations of the inference rules currently employed. For normal tissue, there was no significant difference between plan doses achieved by either automated or manual method. With the application of AI-guided method, the basic parameter adjustment task can be accomplished automatically and a comparable plan dose was achieved in comparison with that achieved by the manual method. Future improvements to incorporate case

Semi-automated segmentation of a glioblastoma multiforme on brain MR images for radiotherapy planning.

PubMed

Hori, Daisuke; Katsuragawa, Shigehiko; Murakami, Ryuuji; Hirai, Toshinori

2010-04-20

We propose a computerized method for semi-automated segmentation of the gross tumor volume (GTV) of a glioblastoma multiforme (GBM) on brain MR images for radiotherapy planning (RTP). Three-dimensional (3D) MR images of 28 cases with a GBM were used in this study. First, a sphere volume of interest (VOI) including the GBM was selected by clicking a part of the GBM region in the 3D image. Then, the sphere VOI was transformed to a two-dimensional (2D) image by use of a spiral-scanning technique. We employed active contour models (ACM) to delineate an optimal outline of the GBM in the transformed 2D image. After inverse transform of the optimal outline to the 3D space, a morphological filter was applied to smooth the shape of the 3D segmented region. For evaluation of our computerized method, we compared the computer output with manually segmented regions, which were obtained by a therapeutic radiologist using a manual tracking method. In evaluating our segmentation method, we employed the Jaccard similarity coefficient (JSC) and the true segmentation coefficient (TSC) in volumes between the computer output and the manually segmented region. The mean and standard deviation of JSC and TSC were 74.2+/-9.8% and 84.1+/-7.1%, respectively. Our segmentation method provided a relatively accurate outline for GBM and would be useful for radiotherapy planning.

Automated analysis of complex data

NASA Technical Reports Server (NTRS)

Saintamant, Robert; Cohen, Paul R.

1994-01-01

We have examined some of the issues involved in automating exploratory data analysis, in particular the tradeoff between control and opportunism. We have proposed an opportunistic planning solution for this tradeoff, and we have implemented a prototype, Igor, to test the approach. Our experience in developing Igor was surprisingly smooth. In contrast to earlier versions that relied on rule representation, it was straightforward to increment Igor's knowledge base without causing the search space to explode. The planning representation appears to be both general and powerful, with high level strategic knowledge provided by goals and plans, and the hooks for domain-specific knowledge are provided by monitors and focusing heuristics.

Automation of On-Board Flightpath Management

NASA Technical Reports Server (NTRS)

Erzberger, H.

1981-01-01

The status of concepts and techniques for the design of onboard flight path management systems is reviewed. Such systems are designed to increase flight efficiency and safety by automating the optimization of flight procedures onboard aircraft. After a brief review of the origins and functions of such systems, two complementary methods are described for attacking the key design problem, namely, the synthesis of efficient trajectories. One method optimizes en route, the other optimizes terminal area flight; both methods are rooted in optimal control theory. Simulation and flight test results are reviewed to illustrate the potential of these systems for fuel and cost savings.

Framework for Human-Automation Collaboration: Conclusions from Four Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oxstrand, Johanna; Le Blanc, Katya L.; O'Hara, John

The Human Automation Collaboration (HAC) research project is investigating how advanced technologies that are planned for Advanced Small Modular Reactors (AdvSMR) will affect the performance and the reliability of the plant from a human factors and human performance perspective. The HAC research effort investigates the consequences of allocating functions between the operators and automated systems. More specifically, the research team is addressing how to best design the collaboration between the operators and the automated systems in a manner that has the greatest positive impact on overall plant performance and reliability. Oxstrand et al. (2013 - March) describes the efforts conductedmore » by the researchers to identify the research needs for HAC. The research team reviewed the literature on HAC, developed a model of HAC, and identified gaps in the existing knowledge of human-automation collaboration. As described in Oxstrand et al. (2013 – June), the team then prioritized the research topics identified based on the specific needs in the context of AdvSMR. The prioritization was based on two sources of input: 1) The preliminary functions and tasks, and 2) The model of HAC. As a result, three analytical studies were planned and conduced; 1) Models of Teamwork, 2) Standardized HAC Performance Measurement Battery, and 3) Initiators and Triggering Conditions for Adaptive Automation. Additionally, one field study was also conducted at Idaho Falls Power.« less

Plan demographics, participants' saving behavior, and target-date fund investments.

PubMed

Park, Youngkyun

2009-05-01

This analysis explores (1) whether plan demographic characteristics would affect individual participant contribution rates and target-date fund investments and (2) equity glide paths for participants in relation to plan demographics by considering target replacement income and its success rate. PLAN DEMOGRAPHIC CHARACTERISTICS IN PARTICIPANT CONTRIBUTION RATES: This study finds empirical evidence that 401(k) plan participants' contribution rates differ by plan demographics based on participants' income and/or tenure. In particular, participants in 401(k) plans dominated by those with low income and short tenure tend to contribute less than those in plans dominated by participants with high income and long tenure. Future research will explore how participant contribution behavior may also be influenced by incentives provided by employers through matching formulae. PLAN DEMOGRAPHIC CHARACTERISTICS IN TARGET-DATE FUND INVESTMENTS: The study also finds empirical evidence that participants' investments in target-date funds with different equity allocations differ by plan demographics based on participants' income and/or tenure. In particular, target-date fund users with 90 percent or more of their account balances in target-date funds who are in 401(k) plans dominated by low-income and short-tenure participants tend to hold target-date funds with lower equity allocations, compared with their counterparts in plans dominated by high-income and long-tenure participants. Future research will focus on the extent to which these characteristics might influence the selection of target-date funds by plan sponsors. EQUITY GLIDE PATHS: Several stylized equity glide paths as well as alternative asset allocations are compared for participants at various starting ages to demonstrate the interaction between plan demographics and equity glide paths/asset allocations in terms of success rates in meeting various replacement income targets. The equity glide path/asset allocation providing

Vervet monkeys use paths consistent with context-specific spatial movement heuristics.

PubMed

Teichroeb, Julie A

2015-10-01

Animal foraging routes are analogous to the computationally demanding "traveling salesman problem" (TSP), where individuals must find the shortest path among several locations before returning to the start. Humans approximate solutions to TSPs using simple heuristics or "rules of thumb," but our knowledge of how other animals solve multidestination routing problems is incomplete. Most nonhuman primate species have shown limited ability to route plan. However, captive vervets were shown to solve a TSP for six sites. These results were consistent with either planning three steps ahead or a risk-avoidance strategy. I investigated how wild vervet monkeys (Chlorocebus pygerythrus) solved a path problem with six, equally rewarding food sites; where site arrangement allowed assessment of whether vervets found the shortest route and/or used paths consistent with one of three simple heuristics to navigate. Single vervets took the shortest possible path in fewer than half of the trials, usually in ways consistent with the most efficient heuristic (the convex hull). When in competition, vervets' paths were consistent with different, more efficient heuristics dependent on their dominance rank (a cluster strategy for dominants and the nearest neighbor rule for subordinates). These results suggest that, like humans, vervets may solve multidestination routing problems by applying simple, adaptive, context-specific "rules of thumb." The heuristics that were consistent with vervet paths in this study are the same as some of those asserted to be used by humans. These spatial movement strategies may have common evolutionary roots and be part of a universal mental navigational toolkit. Alternatively, they may have emerged through convergent evolution as the optimal way to solve multidestination routing problems.

Dynamic Task Assignment and Path Planning of Multi-AUV System Based on an Improved Self-Organizing Map and Velocity Synthesis Method in Three-Dimensional Underwater Workspace.

PubMed

Zhu, Daqi; Huang, Huan; Yang, S X

2013-04-01

For a 3-D underwater workspace with a variable ocean current, an integrated multiple autonomous underwater vehicle (AUV) dynamic task assignment and path planning algorithm is proposed by combing the improved self-organizing map (SOM) neural network and a novel velocity synthesis approach. The goal is to control a team of AUVs to reach all appointed target locations for only one time on the premise of workload balance and energy sufficiency while guaranteeing the least total and individual consumption in the presence of the variable ocean current. First, the SOM neuron network is developed to assign a team of AUVs to achieve multiple target locations in 3-D ocean environment. The working process involves special definition of the initial neural weights of the SOM network, the rule to select the winner, the computation of the neighborhood function, and the method to update weights. Then, the velocity synthesis approach is applied to plan the shortest path for each AUV to visit the corresponding target in a dynamic environment subject to the ocean current being variable and targets being movable. Lastly, to demonstrate the effectiveness of the proposed approach, simulation results are given in this paper.

On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles

DTIC Science & Technology

2006-02-17

On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles Report Title ABSTRACT In this work we proposed two semi-analytic...298-102 Enclosure 1 On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles by...Specifically, the following problems will be addressed during this project: 2.1 Challenges The problem of trajectory planning for high-speed autonomous vehicles is

Space missions for automation and robotics technologies (SMART) program

NASA Technical Reports Server (NTRS)

Ciffone, D. L.; Lum, H., Jr.

1985-01-01

The motivations, features and expected benefits and applications of the NASA SMART program are summarized. SMART is intended to push the state of the art in automation and robotics, a goal that Public Law 98-371 mandated be an inherent part of the Space Station program. The effort would first require tests of sensors, manipulators, computers and other subsystems as seeds for the evolution of flight-qualified subsystems. Consideration is currently being given to robotics systems as add-ons to the RMS, MMU and OMV and a self-contained automation and robotics module which would be tended by astronaut visits. Probable experimentation and development paths that would be pursued with the equipment are discussed, along with the management structure and procedures for the program. The first hardware flight is projected for 1989.

Computing and Office Automation: Changing Variables.

ERIC Educational Resources Information Center

Staman, E. Michael

1981-01-01

Trends in computing and office automation and their applications, including planning, institutional research, and general administrative support in higher education, are discussed. Changing aspects of information processing and an increasingly larger user community are considered. The computing literacy cycle may involve programming, analysis, use…

Manual, semiautomated, and fully automated measurement of the aortic annulus for planning of transcatheter aortic valve replacement (TAVR/TAVI): analysis of interchangeability.

PubMed

Lou, Junyang; Obuchowski, Nancy A; Krishnaswamy, Amar; Popovic, Zoran; Flamm, Scott D; Kapadia, Samir R; Svensson, Lars G; Bolen, Michael A; Desai, Milind Y; Halliburton, Sandra S; Tuzcu, E Murat; Schoenhagen, Paul

2015-01-01

Preprocedural 3-dimensional CT imaging of the aortic annular plane plays a critical role for transcatheter aortic valve replacement (TAVR) planning; however, manual reconstructions are complex. Automated analysis software may improve reproducibility and agreement between readers but is incompletely validated. In 110 TAVR patients (mean age, 81 years; 37% female) undergoing preprocedural multidetector CT, automated reconstruction of the aortic annular plane and planimetry of the annulus was performed with a prototype of now commercially available software (syngo.CT Cardiac Function-Valve Pilot; Siemens Healthcare, Erlangen, Germany). Fully automated, semiautomated, and manual annulus measurements were compared. Intrareader and inter-reader agreement, intermodality agreement, and interchangeability were analyzed. Finally, the impact of these measurements on recommended valve size was evaluated. Semiautomated analysis required major correction in 5 patients (4.5%). In the remaining 95.5%, only minor correction was performed. Mean manual annulus area was significantly smaller than fully automated results (P < .001 for both readers) but similar to semiautomated measurements (5.0 vs 5.4 vs 4.9 cm(2), respectively). The frequency of concordant recommendations for valve size increased if manual analysis was replaced with the semiautomated method (60% agreement was improved to 82.4%; 95% confidence interval for the difference [69.1%-83.4%]). Semiautomated aortic annulus analysis, with minor correction by the user, provides reliable results in the context of TAVR annulus evaluation. Copyright © 2015 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Assessment selection in human-automation interaction studies: The Failure-GAM2E and review of assessment methods for highly automated driving.

PubMed

Grane, Camilla

2018-01-01

Highly automated driving will change driver's behavioural patterns. Traditional methods used for assessing manual driving will only be applicable for the parts of human-automation interaction where the driver intervenes such as in hand-over and take-over situations. Therefore, driver behaviour assessment will need to adapt to the new driving scenarios. This paper aims at simplifying the process of selecting appropriate assessment methods. Thirty-five papers were reviewed to examine potential and relevant methods. The review showed that many studies still relies on traditional driving assessment methods. A new method, the Failure-GAM 2 E model, with purpose to aid assessment selection when planning a study, is proposed and exemplified in the paper. Failure-GAM 2 E includes a systematic step-by-step procedure defining the situation, failures (Failure), goals (G), actions (A), subjective methods (M), objective methods (M) and equipment (E). The use of Failure-GAM 2 E in a study example resulted in a well-reasoned assessment plan, a new way of measuring trust through feet movements and a proposed Optimal Risk Management Model. Failure-GAM 2 E and the Optimal Risk Management Model are believed to support the planning process for research studies in the field of human-automation interaction. Copyright © 2017 Elsevier Ltd. All rights reserved.

Autonomy, Automation, and Systems

NASA Astrophysics Data System (ADS)

Turner, Philip R.

1987-02-01

Aerospace industry interest in autonomy and automation, given fresh impetus by the national goal of establishing a Space Station, is becoming a major item of research and technology development. The promise of new technology arising from research in Artificial Intelligence (AI) has focused much attention on its potential in autonomy and automation. These technologies can improve performance in autonomous control functions that involve planning, scheduling, and fault diagnosis of complex systems. There are, however, many aspects of system and subsystem design in an autonomous system that impact AI applications, but do not directly involve AI technology. Development of a system control architecture, establishment of an operating system within the design, providing command and sensory data collection features appropriate to automated operation, and the use of design analysis tools to support system engineering are specific examples of major design issues. Aspects such as these must also receive attention and technology development support if we are to implement complex autonomous systems within the realistic limitations of mass, power, cost, and available flight-qualified technology that are all-important to a flight project.

Solving a Hamiltonian Path Problem with a bacterial computer

PubMed Central

Baumgardner, Jordan; Acker, Karen; Adefuye, Oyinade; Crowley, Samuel Thomas; DeLoache, Will; Dickson, James O; Heard, Lane; Martens, Andrew T; Morton, Nickolaus; Ritter, Michelle; Shoecraft, Amber; Treece, Jessica; Unzicker, Matthew; Valencia, Amanda; Waters, Mike; Campbell, A Malcolm; Heyer, Laurie J; Poet, Jeffrey L; Eckdahl, Todd T

2009-01-01

Background The Hamiltonian Path Problem asks whether there is a route in a directed graph from a beginning node to an ending node, visiting each node exactly once. The Hamiltonian Path Problem is NP complete, achieving surprising computational complexity with modest increases in size. This challenge has inspired researchers to broaden the definition of a computer. DNA computers have been developed that solve NP complete problems. Bacterial computers can be programmed by constructing genetic circuits to execute an algorithm that is responsive to the environment and whose result can be observed. Each bacterium can examine a solution to a mathematical problem and billions of them can explore billions of possible solutions. Bacterial computers can be automated, made responsive to selection, and reproduce themselves so that more processing capacity is applied to problems over time. Results We programmed bacteria with a genetic circuit that enables them to evaluate all possible paths in a directed graph in order to find a Hamiltonian path. We encoded a three node directed graph as DNA segments that were autonomously shuffled randomly inside bacteria by a Hin/hixC recombination system we previously adapted from Salmonella typhimurium for use in Escherichia coli. We represented nodes in the graph as linked halves of two different genes encoding red or green fluorescent proteins. Bacterial populations displayed phenotypes that reflected random ordering of edges in the graph. Individual bacterial clones that found a Hamiltonian path reported their success by fluorescing both red and green, resulting in yellow colonies. We used DNA sequencing to verify that the yellow phenotype resulted from genotypes that represented Hamiltonian path solutions, demonstrating that our bacterial computer functioned as expected. Conclusion We successfully designed, constructed, and tested a bacterial computer capable of finding a Hamiltonian path in a three node directed graph. This proof

Alternative Paths to Entry: New Jersey and Elsewhere.

ERIC Educational Resources Information Center

Uhler, Sayre

In 1983, New Jersey's governor, Tom Keane, proposed the Alternative Path to Certification as a means to alleviate the state's growing teacher shortage. At least 12 other states are now using similar plans to recruit teachers possessing liberal arts bachelor's degrees who have passed a standardized test and completed successfully a one-year…

Operating and Maintaining Energy Smart Schools Action Plan Template - All Action Plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

none,

2009-07-01

EnergySmart Schools action plan templates for benchmarking, lighting, HVAC, water heating, building envelope, transformer, plug loads, kitchen equipment, swimming pool, building automation system, other.

Learning from Automation Surprises and "Going Sour" Accidents: Progress on Human-Centered Automation

NASA Technical Reports Server (NTRS)

Woods, David D.; Sarter, Nadine B.

1998-01-01

Advances in technology and new levels of automation on commercial jet transports has had many effects. There have been positive effects from both an economic and a safety point of view. The technology changes on the flight deck also have had reverberating effects on many other aspects of the aviation system and different aspects of human performance. Operational experience, research investigations, incidents, and occasionally accidents have shown that new and sometimes surprising problems have arisen as well. What are these problems with cockpit automation, and what should we learn from them? Do they represent over-automation or human error? Or instead perhaps there is a third possibility - they represent coordination breakdowns between operators and the automation? Are the problems just a series of small independent glitches revealed by specific accidents or near misses? Do these glitches represent a few small areas where there are cracks to be patched in what is otherwise a record of outstanding designs and systems? Or do these problems provide us with evidence about deeper factors that we need to address if we are to maintain and improve aviation safety in a changing world? How do the reverberations of technology change on the flight deck provide insight into generic issues about developing human-centered technologies and systems (Winograd and Woods, 1997)? Based on a series of investigations of pilot interaction with cockpit automation (Sarter and Woods, 1992; 1994; 1995; 1997a, 1997 b), supplemented by surveys, operational experience and incident data from other studies (e.g., Degani et al., 1995; Eldredge et al., 1991; Tenney et al., 1995; Wiener, 1989), we too have found that the problems that surround crew interaction with automation are more than a series of individual glitches. These difficulties are symptoms that indicate deeper patterns and phenomena concerning human-machine cooperation and paths towards disaster. In addition, we find the same kinds of

Automation of surface observations program

NASA Technical Reports Server (NTRS)

Short, Steve E.

1988-01-01

At present, surface weather observing methods are still largely manual and labor intensive. Through the nationwide implementation of Automated Surface Observing Systems (ASOS), this situation can be improved. Two ASOS capability levels are planned. The first is a basic-level system which will automatically observe the weather parameters essential for aviation operations and will operate either with or without supplemental contributions by an observer. The second is a more fully automated, stand-alone system which will observe and report the full range of weather parameters and will operate primarily in the unattended mode. Approximately 250 systems are planned by the end of the decade. When deployed, these systems will generate the standard hourly and special long-line transmitted weather observations, as well as provide continuous weather information direct to airport users. Specific ASOS configurations will vary depending upon whether the operation is unattended, minimally attended, or fully attended. The major functions of ASOS are data collection, data processing, product distribution, and system control. The program phases of development, demonstration, production system acquisition, and operational implementation are described.

Intelligent software for laboratory automation.

PubMed

Whelan, Ken E; King, Ross D

2004-09-01

The automation of laboratory techniques has greatly increased the number of experiments that can be carried out in the chemical and biological sciences. Until recently, this automation has focused primarily on improving hardware. Here we argue that future advances will concentrate on intelligent software to integrate physical experimentation and results analysis with hypothesis formulation and experiment planning. To illustrate our thesis, we describe the 'Robot Scientist' - the first physically implemented example of such a closed loop system. In the Robot Scientist, experimentation is performed by a laboratory robot, hypotheses concerning the results are generated by machine learning and experiments are allocated and selected by a combination of techniques derived from artificial intelligence research. The performance of the Robot Scientist has been evaluated by a rediscovery task based on yeast functional genomics. The Robot Scientist is proof that the integration of programmable laboratory hardware and intelligent software can be used to develop increasingly automated laboratories.

Enhanced Automated Guidance System for Horizontal Auger Boring Based on Image Processing

PubMed Central

Wu, Lingling; Wen, Guojun; Wang, Yudan; Huang, Lei; Zhou, Jiang

2018-01-01

Horizontal auger boring (HAB) is a widely used trenchless technology for the high-accuracy installation of gravity or pressure pipelines on line and grade. Differing from other pipeline installations, HAB requires a more precise and automated guidance system for use in a practical project. This paper proposes an economic and enhanced automated optical guidance system, based on optimization research of light-emitting diode (LED) light target and five automated image processing bore-path deviation algorithms. An LED target was optimized for many qualities, including light color, filter plate color, luminous intensity, and LED layout. The image preprocessing algorithm, feature extraction algorithm, angle measurement algorithm, deflection detection algorithm, and auto-focus algorithm, compiled in MATLAB, are used to automate image processing for deflection computing and judging. After multiple indoor experiments, this guidance system is applied in a project of hot water pipeline installation, with accuracy controlled within 2 mm in 48-m distance, providing accurate line and grade controls and verifying the feasibility and reliability of the guidance system. PMID:29462855

Enhanced Automated Guidance System for Horizontal Auger Boring Based on Image Processing.

PubMed

Wu, Lingling; Wen, Guojun; Wang, Yudan; Huang, Lei; Zhou, Jiang

2018-02-15

Horizontal auger boring (HAB) is a widely used trenchless technology for the high-accuracy installation of gravity or pressure pipelines on line and grade. Differing from other pipeline installations, HAB requires a more precise and automated guidance system for use in a practical project. This paper proposes an economic and enhanced automated optical guidance system, based on optimization research of light-emitting diode (LED) light target and five automated image processing bore-path deviation algorithms. An LED light target was optimized for many qualities, including light color, filter plate color, luminous intensity, and LED layout. The image preprocessing algorithm, direction location algorithm, angle measurement algorithm, deflection detection algorithm, and auto-focus algorithm, compiled in MATLAB, are used to automate image processing for deflection computing and judging. After multiple indoor experiments, this guidance system is applied in a project of hot water pipeline installation, with accuracy controlled within 2 mm in 48-m distance, providing accurate line and grade controls and verifying the feasibility and reliability of the guidance system.

Dynamic Modeling and Soil Mechanics for Path Planning of the Mars Exploration Rovers

NASA Technical Reports Server (NTRS)

Trease, Brian

2011-01-01

To help minimize risk of high sinkage and slippage during drives and to better understand soil properties and rover terramechanics from drive data, a multidisciplinary team was formed under the Mars Exploration Rover project to develop and utilize dynamic computer-based models for rover drives over realistic terrains. The resulting system, named ARTEMIS (Adams-based Rover Terramechanics and Mobility Interaction System), consists of the dynamic model, a library of terramechanics subroutines, and the high-resolution digital elevation maps of the Mars surface. A 200-element model of the rovers was developed and validated for drop tests before launch, using Adams dynamic modeling software. The external library was built in Fortran and called by Adams to model the wheel-soil interactions include the rut-formation effect of deformable soils, lateral and longitudinal forces, bull-dozing effects, and applied wheel torque. The paper presents the details and implementation of the system. To validate the developed system, one study case is presented from a realistic drive on Mars of the Opportunity rover. The simulation results match well from the measurement of on-board telemetry data. In its final form, ARTEMIS will be used in a predictive manner to assess terrain navigability and will become part of the overall effort in path planning and navigation for both Martian and lunar rovers.

The role of human-automation consensus in multiple unmanned vehicle scheduling.

PubMed

Cummings, M L; Clare, Andrew; Hart, Christin

2010-02-01

This study examined the impact of increasing automation replanning rates on operator performance and workload when supervising a decentralized network of heterogeneous unmanned vehicles. Futuristic unmanned vehicles systems will invert the operator-to-vehicle ratio so that one operator can control multiple dissimilar vehicles connected through a decentralized network. Significant human-automation collaboration will be needed because of automation brittleness, but such collaboration could cause high workload. Three increasing levels of replanning were tested on an existing multiple unmanned vehicle simulation environment that leverages decentralized algorithms for vehicle routing and task allocation in conjunction with human supervision. Rapid replanning can cause high operator workload, ultimately resulting in poorer overall system performance. Poor performance was associated with a lack of operator consensus for when to accept the automation's suggested prompts for new plan consideration as well as negative attitudes toward unmanned aerial vehicles in general. Participants with video game experience tended to collaborate more with the automation, which resulted in better performance. In decentralized unmanned vehicle networks, operators who ignore the automation's requests for new plan consideration and impose rapid replans both increase their own workload and reduce the ability of the vehicle network to operate at its maximum capacity. These findings have implications for personnel selection and training for futuristic systems involving human collaboration with decentralized algorithms embedded in networks of autonomous systems.

Expert system for neurosurgical treatment planning