Fast and Accurate Relative Motion Tracking for Dual Industrial Robots

TL;DR

This work addresses fast, uniform relative motion tracking for dual industrial robots along 3D curves by formulating exact and relaxed optimization problems that maximize relative traversal speed under kinematic and controller constraints. The proposed solution decomposes the problem into system configuration optimization, motion-primitive fitting with a greedy greedy approach, and iterative waypoint adjustment to satisfy speed and tracking tolerances. Demonstrations on ABB and FANUC platforms (both in simulation and on physical hardware) show large speedups over baseline and single-arm configurations, validating the practicality of the approach despite vendor-specific controller blending. The results inform a scalable workflow for industrial co-robot trajectory programming, enabling higher throughput in processes like coating, welding, and additive manufacturing.

Abstract

Industrial robotic applications such as spraying, welding, and additive manufacturing frequently require fast, accurate, and uniform motion along a 3D spatial curve. To increase process throughput, some manufacturers propose a dual-robot setup to overcome the speed limitation of a single robot. Industrial robot motion is programmed through waypoints connected by motion primitives (Cartesian linear and circular paths and linear joint paths at constant Cartesian speed). The actual robot motion is affected by the blending between these motion primitives and the pose of the robot (an outstretched/near-singularity pose tends to have larger path tracking errors). Choosing the waypoints and the speed along each motion segment to achieve the performance requirement is challenging. At present, there is no automated solution, and laborious manual tuning by robot experts is needed to approach the desired performance. In this paper, we present a systematic three-step approach to designing and programming a dual robot system to optimize system performance. The first step is to select the relative placement between the two robots based on the specified relative motion path. The second step is to select the relative waypoints and the motion primitives. The final step is to update the waypoints iteratively based on the actual measured relative motion. Waypoint iteration is first executed in simulation and then completed using the actual robots. For performance assessment, we use the mean path speed subject to the relative position and orientation constraints and the path speed uniformity constraint. We have demonstrated the effectiveness of this method on two systems, a physical testbed of two ABB robots and a simulation testbed of two FANUC robots, for two challenging test curves.

Figures (11)

• Figure 1: Dual-arm spraying mock-up in simulation and physical testbed.
• Figure 2: Three types of robot motion primitives. moveL: linear in Cartesian Space; moveC: circular arc in Cartesian space, defined by start, end and a circlepoint; moveJ: linear in joint space.
• Figure 3: Curve 1 relative trajectory traversal speed boundary profile based on both arms' joint velocity (blue) and configuration-dependent acceleration constraints (orange). The minimum of both establishes the feasible $\dot\lambda_{\max}$ of the relative trajectory.
• Figure 4: Optimized configuration for the single-arm case icra_singlearm vs. the dual-arm case in this paper.
• Figure 5: Differential evolution optimization progression for the estimated path traversal speed $\mu$ for the two test curves in Section \ref{['sec:curves']}. The final outputs are the complete robot joint trajectories and the robot base relative pose.