Name
Abstract | ||
|---|---|---|
In this paper, we present a software-based approach for collision avoidance that can be applied in human-robot collaboration scenarios. One of the contributions is a method for converting clustered 3D sensor data into computationally efficient convex hull representations used for robot-obstacle distance computation. Based on the computed distance vectors, we generate collision avoidance motions using a potential field approach and integrate them with other simultaneously running robot tasks in a constraint-based control framework. In order to improve control performance, we apply evolutionary techniques for parameter optimization within this framework based on selected quality criteria. Experiments are performed on a dual-arm robotic system equipped with several depth cameras. The approach is able to generate task-compliant avoidance motions in dynamic environments with high performance. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1080/01691864.2020.1721322 | ADVANCED ROBOTICS |
Keywords | Field | DocType |
Collision avoidance,human-robot collaboration,real-time robot control,parameter optimization | Collision,Control engineering,Software,Engineering,Human–robot interaction | Journal |
Volume | Issue | ISSN |
34.0 | 5 | 0169-1864 |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dennis Mronga | 1 | 13 | 2.91 |
| Tobias Knobloch | 2 | 1 | 0.36 |
| Jose de Gea Fernandez | 3 | 10 | 2.26 |
| Frank Kirchner | 4 | 115 | 19.41 |