Abstract
In this paper we show that parallel search techniques derived from their sequential counterparts can enable the solution of instances of the robot motion planning problem that are computationally infeasible on sequential machines. We present a simple parallel version of a robot motion planning algorithm based on "quasi best first" search with randomized escape from local minima and random backtracking and discuss its performance on two problem instances, one of which was computationally infeasible on a single processor of an nCUBE21 multicomputer. We then discuss the limitations of parallel robot motion planning systems, and suggest a course for future work.
| Original language | English (US) |
|---|---|
| Pages | 40-47 |
| Number of pages | 8 |
| State | Published - 1993 |
| Externally published | Yes |
| Event | 1993 AAAI Spring Symposium - Palo Alto, United States Duration: Mar 23 1993 → Mar 25 1993 |
Conference
| Conference | 1993 AAAI Spring Symposium |
|---|---|
| Country/Territory | United States |
| City | Palo Alto |
| Period | 3/23/93 → 3/25/93 |
Bibliographical note
Publisher Copyright:© 1993 AI Access Foundation. All rights reserved.