Vision-based predictive assist control on master-slave systems
Akio Namiki, Yosuke Matsumoto, Tomohiro Maruyama, Yang Liu
- Year
- 2017
- Citations
- 13
Abstract
In this paper, we propose a method for improving the maneuverability of master-slave systems. We aim at reproducing human skillfulness and dynamic performance in master-slave robots by using assist control for human operators. In this paper, we tackle a reaching task performed by a master-slave robot and propose an operation assist algorithm based on visual feedback control. The algorithm consists of visual object recognition for a slave robot, prediction of the operator's motion by a particle filter, estimation of the operator's intention, and operation assistance of the reaching motion. We verified the validity of the proposed system in experiments.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991