Name
Abstract | ||
|---|---|---|
This paper presents a new trajectory planning algorithm based on context-dependent search strategy switching for manipulators working in confined workspaces. This problem has an inherently complex and large search space. Finding good solutions to this problem requires developing an efficient search strategy using appropriately-designed motion primitives and heuristic functions to guide the search. The algorithm presented in this paper monitors the search progress and uses different search strategies in different parts of the search space. This allows it to solve manipulator trajectory planning problems for highly-confined workspaces. It is also able to seek input from the human user when search heuristics are unable to provide guidance to the search process. We present results on challenging example parts and compare them with the previously reported approaches. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/COASE.2018.8560414 | 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) |
Keywords | Field | DocType |
context-dependent search strategy,heuristic functions,search heuristics,search process,manipulators,motion primitives,trajectory planning algorithm | Mathematical optimization,Heuristic,Workspace,Computer science,Manipulator,Heuristics,Trajectory planning | Conference |
ISSN | ISBN | Citations |
2161-8070 | 978-1-5386-3594-0 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ariyan M. Kabir | 1 | 18 | 6.94 |
| Brual C. Shah | 2 | 15 | 4.85 |
| Satyandra K Gupta | 3 | 687 | 77.11 |