Selectively Damped Least Squares for Inverse Kinematics

We introduce two methods for the inverse kinematics of multibodies with multiple end effectors. The first method clamps the distance of the target positions. Experiments show this is effective in reducing oscillation when target positions are unreachable. The second method is an extension of damped least squares called selectively damped least squares (SDLS), which adjusts the damping factor separately for each singular vector of the Jacobian singular value decomposition based on the difficulty of reaching the target positions. SDLS has advantages in converging in fewer iterations and in not requiring ad-hoc damping constants. Source code is available online.