Hand-guide Training Based on Integration of Force Information Obtained by Sensor and State Observer

Abstract

It is important to develop technologies to replace human works with robotic technology to solve the decline in the working population and skilled workers due to the low birthrate and increasing aging population. To preserve and pass on human skillful motions, it is considered that training by hand using a robot is effective. However, it has been difficult to separate the contact force with a target object and a force applied by the trainee to the robot in the hand-guided training system with force sensor-less control. Therefore, it is necessary to divide the robot system for guidance into a master-slave system and separate the action and reaction forces. This study proposes a hand-guided motion training system that uses and integrates two types of force information obtained from a force sensor and a state observer. Since the proposed method can separate the reaction force from the target and the trainee's action force, it is possible to construct a hand-guided motion training system without using a master-slave system. Experiments confirm the effectiveness of the proposed method.