Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
411891 | Robotics and Autonomous Systems | 2009 | 8 Pages |
Abstract
A search methodology with goal state optimization considering computational resource constraints is proposed. The combination of “an extended graph search methodology” and “parallelization of task execution and online planning” makes it possible to solve the problem. The uncertainty of the task execution time is also considered. The problem can be solved by utilizing a random-based and/or a greedy-based graph-searching methodology. The proposed method is evaluated using a rearrangement problem of 20 movable objects with uncertainty in the task execution time, and the effectiveness is shown with simulation results.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Jun Ota,