Name
Title | ||
|---|---|---|
A Framework for Unknown Environment Manipulator Motion Planning via Model Based Realtime Rehearsal. |
Abstract | ||
|---|---|---|
In this paper, we propose a novel framework for an unknown environment path planning of manipulator type robots Unknown environment motion planning, by its nature, requires a sensor based planning approach. The problem domain of unknown environment planning is notoriously hard, especially for difficult cases. The framework we propose herein is a sensor based planner composed of a sequence of multiple MBPs (Model Based Planners) in the notion of cognitive planning using realtime rehearsal. That is, by the proposed framework, one can use a combination of model based planners as tactical tools to resolve location specific problems in overall planning endeavor. The enabling technology for the realtime rehearsal is a sensitive skin type sensor introduced in the paper. We describe the developed sensor and demonstrate the feasibility of solving a difficult unknown environment problem using the introduced sensor based planning framework up to 3 DOF linked manipulator. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-33932-5_58 | INTELLIGENT AUTONOMOUS SYSTEMS 12 , VOL 2 |
Keywords | Field | DocType |
sensor based planning,randomized sampling,unknown environment motion planning,collision avoidance,cognitive planning | Motion planning,Environment Problem,Problem domain,Manipulator motion planning,Planning,Manipulator,Planner,Artificial intelligence,Engineering,Robot | Conference |
Volume | ISSN | Citations |
194 | 2194-5357 | 1 |
PageRank | References | Authors |
0.40 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| D. Um | 1 | 17 | 5.27 |
| Dongseok Ryu | 2 | 66 | 9.79 |
| Sungchul Kang | 3 | 373 | 47.67 |