Energy Efficient Path and Trajectory Optimization of Manipulators With Task Deadline Constraints

Abstract

Improving the energy efficiency of robots is an important issue for the widespread use of robots in society. However, previous methods plan motions to perform tasks in the shortest possible time in consideration of work efficiency. Other methods change the trajectory for same path to decrease unnecessary acceleration/deceleration. On the other hand, it would be efficient to plan a path and trajectory that proceeds to a goal position after waiting in an energy-efficient posture with low joint torque load. The energy-efficient posture is depending on a robot’s structure such as length or mass of each link, joint specifications and a spring of a joint to support weight of a robot. Furthermore, there is a possibility to improve the calculation speed by using quantum computing technology, which can solve combinatorial optimization problems at high speed. In this study, we propose a method for generating low energy-consumption motions for robots using quantum computing technology. The problem is formulated by discretizing the transitions of end-effector positions that represent the robot’s motion in terms of workspace and work time, and by using the total torque required for the motion as an objective function and constraints representing the robot’s performance and the range and time of the target work. Simulation results show that the proposed method reduces the total torque consumption by 10% compared to a simple linear motion, and the computation time could be reduced by 77%. Moreover, a torque consumption reduction of 2% was confirmed compared to the optimized motion without springs.

Keywords

• Robotics
• energy consumption
• optimization
• quantum computing