Resolution Independent Grid-Based Path Planning.

Abstract

Energy conservation in a rover is an important factor which should be considered for a mission of long duration. Locomotion is one of the primary consumers of energy. The energy used depends on the terrain and the path taken by the robot. This paper develops a planning strategy based on cell decomposition and A* algorithm which would minimize power usage due to locomotion. Cell decomposition is used because of its ability to represent the environment as a grid of continuous values. The current limitation with cell decomposition is that the path produced is resolution-optimal only. The method developed in this paper overcomes this problem and produces resolution-independent optimal solutions for a binary (obstacle/free space) environment and better results for the continuously varying environment than common existing techniques. This is done in a computationally efficient manner.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1995
Accession Number
ADA311502

Entities

People

  • Anthony Stentz
  • Gita Krishnaswamy

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Costs
  • Decomposition
  • Efficiency
  • Energy Consumption
  • Environment
  • Geometry
  • Locomotion
  • Models
  • Motion Planning
  • Robotics
  • Robots
  • Sequences
  • Terrain Models
  • Trees (Data Structures)
  • Visibility

Fields of Study

  • Engineering

Readers

  • Computer Vision.
  • Energy Conservation and Renewable Energy Engineering.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Space
  • Space - Spacecraft Maneuvers