학술논문
An analytical diabolo model for robotic learning and control
Document Type
Conference
Author
Source
2021 IEEE International Conference on Robotics and Automation (ICRA) Robotics and Automation (ICRA), 2021 IEEE International Conference on. :4055-4061 May, 2021
Subject
Language
ISSN
2577-087X
Abstract
In this paper, we present a diabolo model that can be used for training agents in simulation to play diabolo, as well as running it on a real dual robot arm system. We first derive an analytical model of the diabolo-string system and compare its accuracy using data recorded via motion capture, which we release as a public dataset of skilled play with diabolos of different dynamics. We show that our model outperforms a deep-learning-based predictor, both in terms of precision and physically consistent behavior. Next, we describe a method based on optimal control to generate robot trajectories that produce the desired diabolo trajectory, as well as a system to transform higher-level actions into robot motions. Finally, we test our method on a real robot system playing the diabolo, and throw it to and catch it from a human player.