Energy Minimization in Time-Constrained Robotic Tasks via Sequential Quadratic Programming

Reduction of the energy consumption in robotized processes is a key issue in nowadays manufacturing. In this paper, we propose a simple approach to energy minimization of robotic tasks with assigned cycle time based on sequential quadratic programming. The method aims at re-shaping a given timing law in the sense of energy saving, without modifying the desired path and the given cycle time. Thanks to the iterative linearization of the nonlinear time-constraint, the resulting minimization problem is solved by only using common quadratic programming solvers, making the method suitable for a direct implementation in robot industrial controllers. At first, the method is devised by only considering the kinematics of the manipulator. The dynamic model is then straightforwardly included, without significantly increasing the complexity of the method. Validation in simulation environment is provided in order to show the effectiveness of the methodology