Energy Assessment and Optimization Methodology for Colaborative Robots

In the past decade, collaborative robots (cobots) have gained popularity for their ability to work safely with humans. Cobots are designed for flexibility, lightweight, and ease of use, making them suitable for various industries and applications. Energy efficiency is a crucial aspect of cobot performance, especially with the growing demand for sustainable technology. To improve this, we evaluated the robot's energy consumption through experimental data obtained from moving the robot's end effector with different payloads in different trajectories. The experimental data were analyzed for three purposes: to develop mathematical models, to perform energy disaggregation, and to conduct energy benchmarking. Our assessment results led to proposed solutions, including code energy consumption feedback, programming recommendations, and cobot energy benchmarking. The feedback on programming code lines helps practitioners to manually optimize code using their practical knowledge. Based on data, pre-designed trajectories available in the robot's onboard computer can be optimized by modifying trajectory parameters. The data from the experiments is utilized to calculate energy efficiency metrics and then it is possible to compare to other similar collaborative robots from different brands. Finally, the techniques obtained from this research are planned to be disseminated using AR.