Convex multi-criteria design optimization of robotic manipulators via sum-of-squares programming

Official URL: http://dx.doi.org/10.1109/IRC.2019.00089

This paper presents a general framework for optimization of robotic manipulators via sums-of-squares (SoS) programming (semidefinite convex optimization) with multiple design objectives. Both kinematic and dynamic performance measures are discussed and an optimization problem for a proof-of-concept robotic manipulator has been formulated. SoS programming is shown to promise advantages as it can provide globally optimal results up to machine precision and scales much better with respect to the number of design variables than other methods which can obtain globally optimal solutions.