Inverse kinematics for autonomous underwater manipulations using weighted damped least squares

Automation using sensor based target recognition increases efficiency for underwater intervention, but may cause a problem to violate the kinematic limitations of the manipulators. In the paper, the kinematic solution based on the weighted damped least squares is investigated to overcome the limitations: workspace limit and singularity, unintended changes of the robot configurations, and joint limits on position and velocity. By designing appropriate cost functions for each limitation, the proposed method provides the kinematic solution optimized in the manner of weighted norm, even when the manipulators meet those limitations. Through the numerical experiments, the performance of the proposed method is verified.