IMPROVING LOCAL TORQUE OPTIMIZATION TECHNIQUES FOR REDUNDANT ROBOTIC MECHANISMS

Two techniques that improve existing local torque optimization methods for redundant robotic mechanisms are proposed. The first technique is based on a balancing scheme, which balances a joint torque norm against a norm of joint accelerations. Expressions have been derived utilizing the Lagrangian multipliers method. The other technique is based on a torque optimization method which minimizes torques through accelerations, obtained from the null-space of the Jacobian matrix. These accelerations are balanced against the minimum-norm acceleration component in order to improve the performance. Numerical simulations have been carried out which in most cases illustrate good performance capability from the viewpoint of torque optimization and global stability.