Energy and peak-power optimization of time-bounded robot trajectories

摘要

This paper, as an outcome of the EU project AREUS, heralds an optimization procedure that reduces up to 30% of energy consumption and up to 60% in peak-power for the trajectories that were tested on a real industrial robot. We have evaluated a number of cost functions and tested our algorithm for a variety of scenarios such as varying cycle times, payloads, and single/two-robot cases. The significance of our work is not only in the impressive savings, simplicity of implementation and preserving path and cycle time, but also in the effort made to carry out the optimization and experiments in as realistic conditions as possible, and the guidelines we provide to achieve this.