Abstract
In this paper, we describe a planning and control approach in terms of sampling using Rapidly-exploring Random Trees (RRTs), which were introduced by LaValle. We review RRTs for motion planning and show how to use them to solve standard nonlinear control problems. We extend them to the case of hybrid systems and describe our modifications to LaValle's Motion Strategy Library to allow for hybrid motion planning. Finally, we extend them to purely discrete spaces (using heuristic evaluation as a distance metric) and provide computational experiments comparing them to conventional methods, such as A*.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 657-663 |
| Number of pages | 7 |
| Journal | Proceedings of the IEEE Conference on Decision and Control |
| Volume | 1 |
| State | Published - 2003 |
| Externally published | Yes |
| Event | 42nd IEEE Conference on Decision and Control - Maui, HI, United States Duration: Dec 9 2003 → Dec 12 2003 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization