Grasping Strategy for Unknown Objects Based on Real-Time Grasp-Stability Evaluation Using Proximity Sensing
Yosuke Suzuki, Ryoya Yoshida, Tokuo Tsuji, Toshihiro Nishimura, Tetsuyou Watanabe
Abstract
This letter proposes a robust grasping strategy for unknown objects by performing non-contact grasp-stability evaluation based on proximity sensing. First, we developed a proximity sensor for a multi-fingered hand. Its features are sensor mounting on a spherical fingertip and coating with transparent resin, which are advantageous for nearest point estimation and fingertip motion generation. Next, we realized consecutive evaluation of grasp-stability based on force-closure with assuming the nearest points to be the contact points. By introducing a high-speed sensing and calculation method, the grasp-stability can be consecutively evaluated and updated as the hand moves around the object. Then, we implemented a grasping strategy that adaptively activates multiple motion-primitives based on the information on the nearest points and the grasp-stability. It executes unknown-object grasping by searching for a pose with high grasp-stability and approaching the fingertip to realize the pose. The effectiveness of the methods was confirmed by actual experiments.
BibTeX
@inproceedings{ral2022_graspingstrategy,
title = {Grasping Strategy for Unknown Objects Based on Real-Time Grasp-Stability Evaluation Using Proximity Sensing},
author = {Yosuke Suzuki and Ryoya Yoshida and Tokuo Tsuji and Toshihiro Nishimura and Tetsuyou Watanabe},
booktitle = {RA-L 2022},
year = {2022}
}