Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
110 tokens/sec
GPT-4o
56 tokens/sec
Gemini 2.5 Pro Pro
44 tokens/sec
o3 Pro
6 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Fast and Accurate Relative Motion Tracking for Dual Industrial Robots (2404.06687v2)

Published 10 Apr 2024 in cs.RO, cs.SY, and eess.SY

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.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (28)
  1. H. Chen, T. Fuhlbrigge, and X. Li, “Automated industrial robot path planning for spray painting process: A review,” in 2008 IEEE International Conference on Automation Science and Engineering, 2008, pp. 522–527.
  2. X. Li, X. Li, S. S. Ge, M. O. Khyam, and C. Luo, “Automatic welding seam tracking and identification,” IEEE Transactions on Industrial Electronics, vol. 64, no. 9, pp. 7261–7271, 2017.
  3. S. Chen, Z. Wang, A. Chakraborty, M. Klecka, G. Saunders, and J. Wen, “Robotic deep rolling with iterative learning motion and force control,” IEEE Robotics and Automation Letters, vol. 5, no. 4, pp. 5581–5588, 2020.
  4. K. Ma, X. Wang, and D. Shen, “Design and experiment of robotic belt grinding system with constant grinding force,” in 2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP), 2018, pp. 1–6.
  5. I. M. Nault, G. D. Ferguson, and A. T. Nardi, “Multi-axis tool path optimization and deposition modeling for cold spray additive manufacturing,” Additive Manufacturing, vol. 38, p. 101779, 2021. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2214860420311519
  6. H. He, C.-l. Lu, Y. Wen, G. Saunders, P. Yang, J. Schoonover, J. Wason, A. Julius, and J. T. Wen, “High-speed high-accuracy spatial curve tracking using motion primitives in industrial robots,” in 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023, pp. 12 289–12 295.
  7. T. Alhart, “Brothers in arms: These robots put a new twist on 3D printing,” 2017. [Online]. Available: https://www.ge.com/news/reports/brothers-arms-robots-put-new-twist-3d-printing
  8. RoboDK Inc. , Robot Machining with RoboDK.
  9. OCTOPUZ, RobotMaster:CAD/CAM for robots (Off-Line Programming). [Online]. Available: https://www.octopuz.com/,
  10. Staubli Faverges , VAL3 REFERENCE MANUALV+ Language User’s Guide.
  11. KUKA Roboter GmbH, SOFTWARE KR C1 / KR C2 / KR C3 Reference Guide.
  12. ABB Robotics, Application manual MultiMove.
  13. FANUC America Corporation, FANUC America Corporation R-30iB and R-30iB Plus Controller MULTI ARM Controller Option Manual.
  14. ——, FANUC America Corporation SYSTEM R-30iB and SYSTEM R-30iB Plus Controller Coordinated Motion Setup and Operations Manual.
  15. YASKAWA MOTOMAN Robotics, DX200 OPTIONSINSTRUCTIONSFOR INDEPENDENT/COORDINATED CONTROL FUNCTION.
  16. J. Wason, “abb_motion_program_exec,” 2022. [Online]. Available: https://github.com/johnwason/abb_motion_program_exec
  17. C.-L. Lu, “fanuc_motion_program_exec,” 2022. [Online]. Available: https://github.com/rpiRobotics/fanuc_motion_program_exec
  18. H. He, “dx200_motion_progam_exec,” 2023. [Online]. Available: https://github.com/rpiRobotics/dx200_motion_progam_exec
  19. S. Chen, “Robot manipulators intelligent motion and force control,” Ph.D. dissertation, Rensselaer Polytechnic Institute, Troy, NY, 2021.
  20. ABB Robotics, Product specification IRB 6640.
  21. ——, Product specification IRB 1200.
  22. H. He, “Robot_acceleration_identification,” 2023. [Online]. Available: https://github.com/rpiRobotics/Robot_Acceleration_Identification
  23. R. Storn and K. Price, “Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces,” Journal of Global Optimization, vol. 11, no. 4, pp. 341–359, Dec 1997. [Online]. Available: https://doi.org/10.1023/A:1008202821328
  24. Y. Wen, H. He, A. Julius, and J. T. Wen, “Motion profile optimization in industrial robots using reinforcement learning,” in 2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2023, pp. 1309–1316.
  25. ABB Robotics, Product manual IRC5.
  26. ——, Operating Manual RobotStudio.
  27. rpiRobotics, “Arm-21-02-f-19-robot-motion-program,” 2022. [Online]. Available: https://github.com/rpiRobotics/ARM-21-02-F-19-Robot-Motion-Program
  28. ROS-Industrial, “Introduction to urdf,” 2017. [Online]. Available: https://industrial-training-master.readthedocs.io/en/melodic/_source/session3/Intro-to-URDF.html
User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (10)
  1. Honglu He (4 papers)
  2. Chen-lung Lu (6 papers)
  3. Glenn Saunders (4 papers)
  4. Pinghai Yang (2 papers)
  5. Jeffrey Schoonover (2 papers)
  6. John Wason (2 papers)
  7. Santiago Paternain (50 papers)
  8. Agung Julius (18 papers)
  9. John T. Wen (13 papers)
  10. Leo Ajdelsztajn (1 paper)

Summary

We haven't generated a summary for this paper yet.

X Twitter Logo Streamline Icon: https://streamlinehq.com