Vision-based Belt Manipulation by Humanoid Robot
Yili Qin, Adrien Escande, Arnaud Tanguy, Eiichi Yoshida
Abstract
Deformable objects are very common around us in our daily life. Because they have infinitely many degrees of freedom, they present a challenging problem in robotics. Inspired by practical industrial applications, we present in this paper our research on using a humanoid robot to take a long, thin and flexible belt out of a bobbin and pick up the bending part of the belt from the ground. By proposing a novel non-prehensile manipulation strategy "scraping" which utilizes the friction between the gripper and the surface of the belt, efficient manipulation can be achieved. In addition, a 3D shape detection algorithm for deformable objects is used during manipulation process. By integrating the novel "scraping" motion and the shape detection algorithm into our multi-objective QP-based controller, we show experimentally humanoid robots can complete this complex task.
BibTeX
@inproceedings{iros2020_visionbasedbeltm,
title = {Vision-based Belt Manipulation by Humanoid Robot},
author = {Yili Qin and Adrien Escande and Arnaud Tanguy and Eiichi Yoshida},
booktitle = {IROS 2020},
year = {2020}
}