Energy Optimization Analysis of Robot Trajectories and Optimization Strategies of Processing Tasks Based on Time-Scaling Functions

Currently, optimizing trajectories is an effective method to reduce energy consumption of robotic manufacturing systems. Nevertheless, energy-efficient trajectory planning of robots has consistently posed a challenge. In this paper, we initially analyzed the energy consumption characteristics of industrial robots in detail. Subsequently, a qualitative analysis was conducted on the systematic modeling process from the general energy consumption model to a time-scaling function-based task energy characteristic model. Furthermore, the influencing factors of task energy coefficients were analyzed in depth, and the energy-saving optimization performance of robotic trajectory modification with time-scaling functions was evaluated via case studies. The results demonstrate that execution time is the primary determinant of energy consumption; moreover, the acceleration and deceleration patterns of end tools also have an influence on energy consumption, but this influence is notably significant in scenarios with shorter execution time only, and is usually smaller than the impact of execution time on energy consumption. Finally, energy-saving optimization strategies of typical processing tasks were proposed after analyzing the optimization hierarchies of robot processing trajectories based on the time-scaling method. This study can provide theoretical bases and technical supports for energy consumption modeling and energy-saving trajectory planning of industrial robots and robotic processing systems.