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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

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

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.

rover↗
NASA NTRS1996

Digital Parallel Processor Array for Optimum Path Planning

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.

Kremeny, Sabrina E.↗
NASA NTRS1990

Path planning and execution monitoring for a planetary rover

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.

Gat, Erann↗
NASA NTRS2021

Machine Learning Based Path Planning for Improved Rover Navigation

Enhanced AutoNav (ENav), the baseline surface navigation software for NASA’s Perseverance rover, sorts a list of candidate paths for the rover to traverse, then uses the Approximate Clearance Evaluation (ACE) algorithm to evaluate whether the most highly ranked paths are safe. ACE is crucial for maintaining the safety of the rover, but is computationally expensive. If the most promising candidates in the list of paths are all found to be infeasible, ENav must continue to search the list and run time-consuming ACE evaluations until a feasible path is found. In this paper, we present two heuristics that, given a terrain heightmap around the rover, produce cost estimates that more effectively rank the candidate paths before ACE evaluation. The first heuristic uses Sobel operators and convolution to incorporate the cost of traversing high-gradient terrain. The second heuristic uses a machine learning (ML) model to predict areas that will be deemed untraversable by ACE. We used physics simulations to collect training data for the ML model and to run Monte Carlo trials to quantify navigation performance across a variety of terrains with various slopes and rock distributions. Compared to ENav's baseline performance, integrating the heuristics can lead to a significant reduction in ACE evaluations and average computation time per planning cycle, increase path efficiency, and maintain or improve the rate of successful traverses. This strategy of targeting specific bottlenecks with ML while maintaining the original ACE safety checks provides an example of how ML can be infused into planetary science missions and other safety-critical software.

Yue, Yisong↗
NASA NTRS1987

Robot path planning with distance-safety criterion

A method for determining an optimal path with a weighted distance-safety criterion is developed. The goal is to strike a compromise between the shortest path and the centerline path, which is safer. The method is composed of three parts: (i) construction of a region map by dividing the workspace, (ii) interregion optimization to determine the entry and departure points of the path in each region, and (iii) intraregion optimization for determining the (optimal) path segment within each region. The region map is generated by using an approximate Voronoi diagram, and region optimization is achieved using variational dynamic programming. Although developed for 2-D problems, the method can be easily extended to a class of 3-D problems. Numerical examples are presented to demonstrate the method.

Suh, Suk-Hwan↗
NASA NTRS1990

Navigation path planning for autonomous aircraft - Voronoi diagram approach

The present technique for generating a search graph depicting topologically unique paths around mountain boundaries at constant altitudes involves a description of mountain boundaries as polygons; the search graph is then generated on the basis of a geometric construct. All nodes and arcs of the search graph are guaranteed to lie in free space, thereby ensuring an autonomous aircraft's avoidance of mountain obstacles. The solution path is generated by searching the graph for the optimal path from a start location to a finish location.

Krozel, Jimmy↗
NASA NTRS1989

Off-line robot programming and graphical verification of path planning

The objective of this project was to develop or specify an integrated environment for off-line programming, graphical path verification, and debugging for robotic systems. Two alternatives were compared. The first was the integration of the ASEA Off-line Programming package with ROBSIM, a robotic simulation program. The second alternative was the purchase of the commercial product IGRIP. The needs of the RADL (Robotics Applications Development Laboratory) were explored and the alternatives were evaluated based on these needs. As a result, IGRIP was proposed as the best solution to the problem.

Tonkay, Gregory L.↗
NASA NTRS1990

Real-time fuzzy inference based robot path planning

This project addresses the problem of adaptive trajectory generation for a robot arm. Conventional trajectory generation involves computing a path in real time to minimize a performance measure such as expended energy. This method can be computationally intensive, and it may yield poor results if the trajectory is weakly constrained. Typically some implicit constraints are known, but cannot be encoded analytically. The alternative approach used here is to formulate domain-specific knowledge, including implicit and ill-defined constraints, in terms of fuzzy rules. These rules utilize linguistic terms to relate input variables to output variables. Since the fuzzy rulebase is determined off-line, only high-level, computationally light processing is required in real time. Potential applications for adaptive trajectory generation include missile guidance and various sophisticated robot control tasks, such as automotive assembly, high speed electrical parts insertion, stepper alignment, and motion control for high speed parcel transfer systems.

Pacini, Peter J.↗
NASA NTRS1991

Path planning algorithms for assembly sequence planning

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.

Krishnan, S. S.↗
NASA NTRS1993

Path planning using optically computed potential fields

An algorithm for the optical computation of potential field maps suitable for mobile robot navigation is described and experimentally produced maps and paths are presented. The parallel analog optical computation employs a two-dimensional spatial light modulator on which an image of the potential field map is generated. Optically calculated fields contain no local minima, tend to produce paths centered in gaps between obstacles, and produce paths which give preference to wide gaps. Calculation of 128 x 128 pixel fields at a few hertz are possible with current technology, and calculation time vs. map size scales favorably in comparison to digital electronic computation.

Reid, Max B.↗
NASA NTRS2015

Risk-Aware Planetary Rover Operation: Autonomous Terrain Classification and Path Planning

Identifying and avoiding terrain hazards (e.g., soft soil and pointy embedded rocks) are crucial for the safety of planetary rovers. This paper presents a newly developed groundbased Mars rover operation tool that mitigates risks from terrain by automatically identifying hazards on the terrain, evaluating their risks, and suggesting operators safe paths options that avoids potential risks while achieving specified goals. The tool will bring benefits to rover operations by reducing operation cost, by reducing cognitive load of rover operators, by preventing human errors, and most importantly, by significantly reducing the risk of the loss of rovers.

Ono, Masahiro↗
NASA NTRS1987

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

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.

Smith, Terence R.↗
NASA NTRS1989

Robot path planning with obstacles, actuator, gripper, and payload constraints

A method is presented to obtain the time-optimal motions for robotic manipulators. It considers the full nonlinear dynamics of the manipulator, its actuator saturation limits, and gripper and payload constraints. It also accounts for both the presence of obstacles in the work space and restrictions on the motion of the manipulator's joints. The method is computationally practical and has been implemented for the optimal trajectory planning of general six degree-of-freedom manipulators. Examples are presented that demonstrate the substantial improvement in manipulator performance that can be achieved using this method.

Shiller, Zvi↗
NASA NTRS1990

On the dynamics of space manipulators using the Virtual Manipulator, with applications to path planning

Robotic manipulators carried by future spacecraft are expected to perform important tasks in space, such as the servicing of satellites. However, the performance of these systems could be severely degraded by dynamic disturbances to the spacecraft caused by manipulator motions. This paper presents a method for representing the dynamics of space manipulator systems using the recently developed Virtual Manipulator (VM) concept. This representation is then applied to develop algorithms which can be used to plan manipulator motions that minimize disturbances of the spacecraft.

Vafa, Z.↗
NASA NTRS1990

A testbed for the evaluation of computer aids for enroute flight path planning

A simulator study of the five airline flight crews engaged in various enroute planning activities has been conducted. Based on a cognitive task analysis of this data, a flight planning workstation has been developed on a Mac II controlling three color monitors. This workstation is being used to study design concepts to support the flight planning activities of dispatchers and flight crews in part-task simulators.

Smith, Philip J.↗
NASA NTRS1993

Rectangular Array Of Digital Processors For Planning Paths

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.

Kemeny, Sabrina E.↗