Name
Abstract | ||
|---|---|---|
Randomized motion planners are greatly aected by the eciency and robustness of algorithms for collision checking of robot congurations. A number of powerful collision detection algorithms are currently available to the research community although their relative capabili- ties and performance cannot be easily compared due to the many factors involved. We have experimentally evaluated collision detection packages within the context of motion planning for rigid and articulated robots in 3D workspaces. Articial and realistic problems have been chosen as benchmarks to as- sess package behavior with dierent object models. Re- ported experimental results should help the user in choos- ing the appropriate collision detection package. In this paper we also present the framework we exploited in our planner to allow pluggable distance computation func- tions and keep the code simple and easy to maintain. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/IRDS.2002.1041615 | IROS |
Keywords | Field | DocType |
collision avoidance,robots,robust control,software packages,3D workspaces,articulated robots,collision checking,collision detection packages,randomized motion planners,rigid robots,robot configurations,robot motion planning,robustness | Motion planning,Computer vision,Robot control,Collision detection,Computer science,Workspace,Simulation,Robustness (computer science),Artificial intelligence,Robust control,Robot,Computation | Conference |
Volume | Citations | PageRank |
3 | 14 | 1.33 |
References | Authors | |
17 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Monica Reggiani | 1 | 184 | 24.91 |
| Mirko Mazzoli | 2 | 14 | 1.33 |
| Stefano Caselli | 3 | 314 | 36.32 |