Co-Optimization of Tool Orientations, Kinematic Redundancy, and Waypoint Timing for Robot-Assisted Manufacturing

TL;DR

This paper introduces a scalable, concurrent trajectory optimization method for robot-assisted manufacturing that simultaneously refines tool orientations, kinematic redundancy, and waypoint timing to enhance manufacturing quality and efficiency.

Contribution

It presents a novel, integrated optimization approach that handles large waypoint data efficiently through decomposition and parallel processing, unlike previous decoupled methods.

Findings

Improved kinematic smoothness in robot trajectories.

Enhanced efficiency via parallelized optimization scheme.

Validated effectiveness through simulations and physical experiments.

Abstract

In this paper, we present a concurrent and scalable trajectory optimization method to improve the quality of robot-assisted manufacturing. Our method simultaneously optimizes tool orientations, kinematic redundancy, and waypoint timing on input toolpaths with large numbers of waypoints to improve kinematic smoothness while incorporating manufacturing constraints. Differently, existing methods always determine them in a decoupled manner. To deal with the large number of waypoints on a toolpath, we propose a decomposition-based numerical scheme to optimize the trajectory in an out-of-core manner, which can also run in parallel to improve the efficiency. Simulations and physical experiments have been conducted to demonstrate the performance of our method in examples of robot-assisted additive manufacturing.