Trajectory Optimization of Robots with Regenerative Drive Systems: Numerical and Experimental Results
This work addresses energy efficiency for robotic systems with regenerative drives, but it is incremental as it builds on a previously introduced framework.
The study tackled energy-optimal control for robots with ultracapacitor-based regenerative drive systems, formulating an optimal control problem to maximize energy regeneration and storage, and experimental results on a PUMA 560 manipulator showed a 13% reduction in energy consumption.
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.