Optimizing link-length fitting between an operator and a robot with compensation for habitual movements

Abstract

Teleoperation has become increasingly important for the real-world application of robots. However, in current teleoperation applications, operators need to visually recognize any physical deviations between the robot and themselves and correct its operation accordingly. Even when humans move their bodies, achieving high positional accuracy can be difficult for them, which can limit their speed of movement and place a heavy burden on them. In this study, we proposed a parameter optimization method for feedforward compensation of the link-length deviation and operator's habitual body movements in leader–follower control in 3D space. To optimize the parameters, we used Digital Annealer developed by Fujitsu Ltd, which could rapidly solve the combinatorial optimization problem. The objective function minimized the difference between the hand positions of the robot and targets. Simulations verified that the proposed method could reduce hand positional differences.