A New Extended SDLS to Deal with the JLA in the Inverse Kinematics of an Anthropomorphic Robotic Hand

Abstract

This paper proposes Extending the Selectively Damped Least Squares method to cater for joint limits avoidance (JLA) when solving the inverse kinematics of anthropomorphic robotic hands. Here, the SDLS is considered as the main task allowing to avoid singularity behaviors by computing for each singular value an appropriate damping factor of a Jacobian matrix concatenating the proper kinematics of the robotic hand with an additional task (JLA) projected into the null-space of the main task. A comparative study of different orders-norm of the objective function defining the JLA task has been done with the aim to select the suitable order which is able to overcome the mentioned constraints with less instability and errors. After an initial tuning to choose the right parameters, the method was applied to calculate the kinematics of all fingers’ joints of a robotic hand to fulfill a grasping task. The method achieves the solution of all fingers together as one complex multibody system.KeywordsHand Inverse kinematicssingularity and joint limits avoidanceredundancySVD