Optimum trajectory planning for industrial robots through inverse dynamics

This paper presents a method for developing robot trajectories that achieve minimum energy consumption for a point-to-point motion under kinematic and dynamic constraints. The method represents trajectories as a fourth degree B-spline function. The parameters of the function are optimised using a multi-parametric optimization algorithm. Actuator torques have been considered for the formulation of the cost function, which utilizes an inverse dynamics analysis. Compared to other trajectory optimization techniques, the proposed method allows kinematic and dynamic constraints to be included in the cost function. Thus, the complexity and computational effort of the optimization algorithm is reduced. A two-link simulated robot manipulator is used to demonstrate the effectiveness of the method.