Path planning for highly redundant manipulators using a continuous model

Authors:
Akira Hayashi;Benjamin J. Kuipers
Affiliations:
Department of Computer Sciences, The University of Texas at Austin, Austin, TX;Department of Computer Sciences, The University of Texas at Austin, Austin, TX
Venue:
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 2
Year:
1991

Citing 7
Cited 0

Real-time obstacle avoidance for manipulators and mobile robots

International Journal of Robotics Research
Structuring Free Space as a Hypergraph for Roving Robot Path Planning and Navigation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Some algebraic and geometric computations in PSPACE

STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
Geometrical motion planning for highly redundant manipulators using a continuous model

Geometrical motion planning for highly redundant manipulators using a continuous model
Fundamentals of Robot Technology

Fundamentals of Robot Technology
Spatial Planning: A Configuration Space Approach

IEEE Transactions on Computers
Design of a snake-like manipulator

Robotics and Autonomous Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

There is a need for highly redundant manipulators to work in complex, cluttered environments. Our goal is to plan paths for such manipulators efficiently. The path planning problem has been shown to be PSP ACE-complete in terms of the number of degrees of freedom (DOF) of the manipulator. We present a method which overcomes the complexity with a strong heuristic: utilizing redundancy by means of a continuous manipulator model. The continuous model allows us to change the complexity of the problem from a function of both the DOF of the manipulator (believed to be exponential) and the complexity of the environment (polynomial), to a polynomial function of the complexity of the environment only.