Name
Abstract | ||
|---|---|---|
Robotic assembly requires a system that can handle a wide range of the object poses for the complexity of real-world tasks. One problem during the handling is the uncertain pose of grasped objects. Objects might be grasped differently from simulation and change significantly due to unexpected contact and collisions. In this paper, we propose a visually guided extrinsic manipulation system to tackle these problems. Extrinsic manipulation enhances simple grippers dexterity to precisely reorient objects into target poses required for the assembly tasks through the interaction with a designed extrinsic manipulation platform. Closed loop manipulation is realized through the visual feedback which is provided to the system through AR markers fixed on the object. Experiments show that the proposed system can successfully handle arbitrary initial and final poses of the grasped object, and can correct and restore the uncertain object poses. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICARM.2019.8833631 | 2019 IEEE 4TH INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS AND MECHATRONICS (ICARM 2019) |
Field | DocType | Citations |
Computer vision,Computer science,Artificial intelligence,Grippers | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohamed Raessa | 1 | 3 | 1.73 |
| Damien Petit | 2 | 10 | 3.29 |
| Wan Weiwei | 3 | 127 | 36.02 |
| Kensuke Harada | 4 | 1967 | 172.97 |