Movement Optimization of Robotic Arms for Energy and Time Reduction using Evolutionary Algorithms

TL;DR

This paper presents an evolutionary algorithm-based approach to optimize robotic arm trajectories, reducing energy consumption and improving efficiency, demonstrated on a UR5 robot with significant energy savings.

Contribution

It introduces a particle swarm optimization method for trajectory energy minimization, enhancing robotic arm efficiency and longevity.

Findings

Achieved 49% energy efficiency improvement on UR5 robot.

Validated the method on different trajectories.

Demonstrated energy reduction leads to longer robot lifespan.

Abstract

Trajectory optimization of a robot manipulator consists of both optimization of the robot movement as well as optimization of the robot end-effector path. This paper aims to find optimum movement parameters including movement type, speed, and acceleration to minimize robot energy. Trajectory optimization by minimizing the energy would increase the longevity of robotic manipulators. We utilized the particle swarm optimization method to find the movement parameters leading to minimum energy consumption. The effectiveness of the proposed method is demonstrated on different trajectories. Experimental results show that 49% efficiency was obtained using a UR5 robotic arm.