Approaches for heuristically biasing RRT growth
- 22 March 2004
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1178-1183
- https://doi.org/10.1109/iros.2003.1248805
Abstract
This paper presents several modifications to the basic rapidly-exploring random tree (RRT) search algorithm. The fundamental idea is to utilize a heuristic quality function to guide the search. Results from a relevant simulation experiment illustrate the benefit and drawbacks of the developed algorithms. The paper concludes with several promising directions for future research.Keywords
This publication has 5 references indexed in Scilit:
- Real-time randomized path planning for robot navigationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Optimal and efficient path planning for partially-known environmentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Quasi-randomized path planningPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Real-Time Motion Planning for Agile Autonomous VehiclesJournal of Guidance, Control, and Dynamics, 2002
- Probabilistic roadmaps for path planning in high-dimensional configuration spacesIEEE Transactions on Robotics and Automation, 1996