Minimization of the Energy Consumption in Motion Planning for Single-robot Tasks

Recently, the importance of sustainable manufacturing has been widely discussed. The optimization of energy consumption in product manufacture has been deeply analyzed, mainly focusing on the energy directly absorbed by the manufacturing process. On the contrary, this paper focuses on the analysis and optimization of the energy consumption related to auxiliary robotic assembly processes, contributing to the identification of sustainable manufacturing strategies for pick and place robots. It proposes a methodology for the automatic generation of robot trajectories and the sequencing of the robot task, while minimizing the energy consumption. A probabilistic roadmap is created to identify a collision-free and minimum energy consumption trajectory for each couple of feasible tasks. Trajectory power consumption is evaluated exploiting dynamic information coming from the real robot motion planner using a model that takes into account the energy behavior of motors and drives and their operative conditions. A set of generated trajectories is selected, defining the task sequence and minimizing the robot cycle time. The differences between the results deriving by employment of the energy consumption minimization criterion versus time minimization criterion are presented through a simplified case.