抄録
Operation of tools has long been studied in robotics. Although appropriate hold of the tool by robots is the base of successful tool operation, it is not with ease especially for tools with complicated shape. In this paper, an assist system for a four-limbed robot is proposed for remote operation of reaching and grasping electric drills using deep reinforcement learning. Through comparative evaluation experiments, the increase of success rate for reaching and grasping is verified and the decrease in both physical and mental workload of the operator is also validated by the index of NASA-TLX.
本文言語 | English |
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ページ(範囲) | 365-376 |
ページ数 | 12 |
ジャーナル | Robotica |
巻 | 40 |
号 | 2 |
DOI | |
出版ステータス | Published - 2022 2月 4 |
ASJC Scopus subject areas
- 制御およびシステム工学
- ソフトウェア
- 数学 (全般)
- コンピュータ サイエンスの応用