Name
Abstract | ||
|---|---|---|
This work addresses the problem of object delivery with a mobile robot in real-world environments. We introduce a multilayer, modular pushing skill that enables a robot to push unknown objects in such environments. We present a strategy that guarantees obstacle avoidance for object delivery by introducing the concept of a pushing corridor. This allows pushing objects in scattered and dynamic environments while exploiting the available collision-free area. Moreover, to push unknown objects, we propose an adaptive pushing controller that learns local inverse models of robot-object interaction on the fly. We performed exhaustive tests showing that our controller can adapt to various unknown objects with different mass and friction distributions. We show empirically that the proposed pushing skill leads towards successful pushes without prior knowledge and experience. The experimental results also demonstrate that the robot can successfully deliver objects in complex scenarios. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/s10514-018-9804-8 | Autonomous Robots |
Keywords | Field | DocType |
Nonprehensile manipulation, Pushing skill, Adaptation, Robot learning | Obstacle avoidance,Robot learning,Computer vision,Control theory,Computer science,On the fly,Artificial intelligence,Modular design,Robot,Mobile robot | Journal |
Volume | Issue | ISSN |
43.0 | 6 | 1573-7527 |
Citations | PageRank | References |
0 | 0.34 | 26 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Senka Krivic | 1 | 10 | 5.03 |
| Justus H. Piater | 2 | 543 | 61.56 |