Name
Abstract | ||
|---|---|---|
Although Rapidly-exploring Random Trees (RRTs) have been successfully applied in path planning of robots with many degrees of freedom under non-holonomic and differential constraints, rapidly identifying and passing through narrow passages in a robot's configuration space remains a challenge for RRTs-based planners. This paper presents a novel two-stage approach to address the problem of multi-d.o.f. robot path planning in high-dimensional configuration space with narrow corridors. The first stage introduces an efficient sampling algorithm called Bridge Test to find a global roadmap that identifies the critical region. The second stage presents two varieties of RRTs, called Triple-RRTs, to search for a local connection under the guidance of the global landmark. The two-stage strategy keeps a fine balance between global heuristics and local connection, resulting in high performance over the previous RRTs-based path planning methods. We have implemented the Triple-RRTs planners for both rigid and articulated robots in two- and three-dimensional environments. Experimental results demonstrate the effectiveness of the proposed method. (C) Koninklijke Brill NV, Leiden and The Robotics Society of Japan, 2010 |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1163/016918610X496928 | ADVANCED ROBOTICS |
Keywords | Field | DocType |
Robot,path planning,Rapidly-exploring Random Trees,narrow passages,multi-d.o.f. | Motion planning,Mathematical optimization,Monad (category theory),Effective method,Heuristics,Sampling (statistics),Robot,Landmark,Mathematics,Configuration space | Journal |
Volume | Issue | ISSN |
24 | 7 | 0169-1864 |
Citations | PageRank | References |
5 | 0.46 | 3 |
Authors | ||
5 | ||