A supervisory control system for a multi-fingered robotic hand using datagloves and a haptic device

This paper describes a supervisory control system for a multi-fingered robotic hand. The proposed method enables a slave robotic hand to grasp an object in a remote environment in several ways, manipulate it, and mimic several non-grasping motions. The key components of the proposed control system are a grasping selector in the master system and motion controllers and a controller selector in the slave system. The grasping selector learns to detect motions commanded by an operator using datagloves. We developed two methods to learn the operator´s hand shapes, one that prioritizes the learning time and one that prioritizes the probability of correct detection. The controller selector determines the current command and awaits a transition, while the motion controllers stably realize the currently commanded motion. We have demonstrated the stable operation of a three-fingered robotic hand using the proposed method.