Matrix normalization for optimal robot design

摘要

Good robot performance often relies upon the selection of design parameters that lead to a well conditioned Jacobian or impedance "design" matrix. In this paper a new design matrix normalization technique is presented to cope with the problem of nonhomogeneous physical units. The technique pre and post-multiplies a design matrix by diagonal scaling matrices corresponding to the range of joint and task space variables. In the case of the Jacobian, normalization leads to a practical interpretation of a robot's "characteristic length" as the desired ratio between maximum linear and angular force or velocity. The scale factors can also be used to set relative required strength or speed along any axes of end-point motion and/or can be treated as free design parameters to improve isotropy through asymmetric actuation. The effect of scaling on actual designs is illustrated by a number of design examples using a global search method previously developed by the authors.