Improving productivity using a multi-objective optimization of robotic trajectory planning

Abstract

This study presents a methodology to tackle robot tasks in a cost-efficientway. It poses amulti-objective optimization problemfor trajectory planning of robotic arms that an efficient algorithmwill solve. Themethod finds the minimum time to perform robot tasks while considering the physical constraints of the real working problem and the economic issues participating in the process. This process also considers robotic system dynamics and the presence of obstacles to avoid collisions. It generates an entire set of equally optimal solutions for each process, the Pareto-optimal frontiers. They provide information about the trade-offs between the different decision variables of the multi-objective optimization problem. This procedure can help managers in decision-making processes regarding performing tasks, items to be manufactured or robotic services performed to meet with the current demand, and also, to define an efficient scheduling. It improves productivity and allows firms to stay competitive in rapid changing markets.