A Method for Minimizing Energy Consumption of Industrial Robots with Cycle Time Considerations
Résumé
This study presents a novel approach to optimizing energy-efficient path planning for industrial robots, focusing on minimizing energy consumption while adhering to cycle time constraints. Simulations were carried out on a virtual FANUC R-2000iB/250F robot within an industrial scenario. The method begins by analyzing the influence of key variables, such as speed, acceleration, waypoint positioning, and termination types, on both energy consumption and cycle time. A statistical model of these two responses was developed, followed by the application of a genetic algorithm to determine the optimal parameters that minimize energy consumption, either by maintaining the cycle time within a predefined range or by simultaneously minimizing it, resulting in a Pareto front of optimal solutions. Validation tests revealed an average 23% reduction in energy consumption compared to non-optimized settings, while maintaining constant cycle time. These results demonstrate the strong potential of the proposed method for industrial applications.