A Planning Framework for Robotic Insertion Tasks via Hydroelastic Contact Model

Robotic contact-rich insertion tasks present a significant challenge for motion planning due to the complex force interaction between robots and objects. Although many learning-based methods have shown success in contact tasks, most methods need sampling or exploring to gather sufficient experimenta...

詳細記述

書誌詳細

出版年:	Machines
主要な著者:	Lin Yang, Mohammad Zaidi Ariffin, Baichuan Lou, Chen Lv, Domenico Campolo
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2023-07-01
主題:	peg-in-hole assembly motion planning contact tasks Dynamic Movement Primitives Black-Box Optimization hydroelastic contact model
オンライン･アクセス:	https://www.mdpi.com/2075-1702/11/7/741