Name
Title | ||
|---|---|---|
Adaptive Neural Admittance Control For Collision Avoidance In Human-Robot Collaborative Tasks |
Abstract | ||
|---|---|---|
This paper proposed an adaptive neural admittance control strategy for collision avoidance in human-robot collaborative tasks. In order to ensure that the robot end-effector can avoid collisions with surroundings, robot should be operated compliantly by human within a constrained task space. An impedance model and a soft saturation function are employed to generate a differentiable reference trajectory. Then, adaptive neural network control with position constraint, based on integral barrier Lyapunov function (IBLF), is designed to achieve precise tracking while guaranteeing constrained satisfaction. Utilizing Lyapunov stability principles, we prove that semi-globally uniformly bounded stability is guaranteed for all states of the closed-loop system. At last, the effectiveness of the proposed algorithm is verified on a Baxter robot experimental platform. Collisions with surroundings can be avoided in human-robot collaborative tasks. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/IROS40897.2019.8967720 | 2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) |
Field | DocType | ISSN |
Computer science,Lyapunov stability,Uniform boundedness,Control engineering,Collision,Robot,Artificial neural network,Admittance,Human–robot interaction,Trajectory | Conference | 2153-0858 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinbo Yu | 1 | 46 | 3.99 |
| wei he | 2 | 2061 | 102.03 |
| Chengqian Xue | 3 | 33 | 2.08 |
| Bin Li | 4 | 0 | 0.34 |
| Long Cheng | 5 | 1492 | 73.97 |
| Chenguang Yang | 6 | 2213 | 138.71 |