Name
Abstract | ||
|---|---|---|
This paper presents the application of an action module planning method to an experimental climbing robot named LIBRA. The method searches for a sequence of physically realizable actions, called action modules, to produce a plan for a given task. The search is performed with a hierarchical selection process that uses task and configuration filters to reduce the action module inventory to a reasonable search space. Then, a genetic algorithm search finds a sequence of actions that allows the robot to complete the task without violating any physical constraints. The results for the LIBRA climbing robot show the method is able to produce effective plans. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1109/ROBOT.2000.845356 | ICRA |
Keywords | Field | DocType |
actuators,search space,genetic algorithm,mobile robots,motion planning,path planning,mechanical engineering,genetic algorithms,ducts | Motion planning,Climbing robots,Control engineering,Artificial intelligence,Engineering,Robot,Genetic algorithm,Mobile robot,Actuator | Conference |
Volume | Issue | ISSN |
4 | 1 | 1050-4729 |
Citations | PageRank | References |
17 | 1.17 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| David M. Bevly | 1 | 188 | 27.06 |
| Shane Farritor | 2 | 163 | 22.86 |
| Steven Dubowsky | 3 | 1365 | 260.81 |