Trajectory Optimization of Robots with Regenerative Drive Systems: Numerical and Experimental Results

TL;DR

This paper presents a method for optimizing robot trajectories to maximize energy regeneration using ultracapacitor-based systems, validated through numerical solutions and experiments on a PUMA 560 robot, achieving significant energy savings.

Contribution

It introduces a generic optimal control framework for energy regeneration in robots with regenerative drive systems, validated through numerical and experimental results.

Findings

Optimal trajectories increase energy regeneration.

Experimental results show 13% reduction in energy consumption.

Validated approach on a PUMA 560 manipulator.

Abstract

We investigate energy-optimal control of robots with ultracapacitor based regenerative drive systems. Based on a previously introduced framework, a fairly generic model is considered for the robot and the drive system. An optimal control problem is formulated to find point-to point trajectories maximizing the amount of energy regenerated and stored in the capacitor. The optimization problem, its numerical solution and an experimental evaluation are demonstrated using a PUMA 560 manipulator. A comprehensive experimental setup was prepared to evaluate power flows and energy regeneration. Tracking of optimal trajectories was enforced on the robot using a standard robust passivity based control approach. Experimental results show that when following optimal trajectories, a reduction of about 13\% in energy consumption can be achieved for the conditions of the study.