Title :
A probability-based approach to model-based path planning
Author :
Mantegh, I. ; Jenkin, M.R.M. ; Goldenberg, A.A.
Author_Institution :
Robotics & Autom. Lab., Toronto Univ., Ont., Canada
Abstract :
By capitalizing on the known properties of harmonic potential functions this work develops a new approach to probability-based path planning that is intuitive, free from local traps (local minima) and computationally less complex than many existing methods. Although the approach presented here is based on the hill-climbing method, it is still able to guarantee goal attainment. Furthermore the algorithm presented here is able to handle arbitrary-shaped geometries and does not require any geometrical or topological approximation at the environment representation level
Keywords :
computational complexity; path planning; probability; robots; arbitrary-shaped geometries; computational complexity; environment representation; harmonic potential functions; hill-climbing method; local minima; model-based path planning; probability-based path planning; robots; Automation; Collision avoidance; Computational geometry; Computer science; Industrial engineering; Intelligent robots; Laboratories; Mechanical factors; Orbital robotics; Path planning;
Conference_Titel :
Intelligent Robots and Systems, 1997. IROS '97., Proceedings of the 1997 IEEE/RSJ International Conference on
Conference_Location :
Grenoble
Print_ISBN :
0-7803-4119-8
DOI :
10.1109/IROS.1997.655160