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JRM Vol.35 No.6 pp. 1583-1592
doi: 10.20965/jrm.2023.p1583
(2023)

Paper:

Robust Cooperative Transport System with Model Error Compensator Using Multiple Robots with Suction Cups

Nobutomo Matsunaga* ORCID Icon, Kazuhi Murata**, and Hiroshi Okajima* ORCID Icon

*Faculty of Advanced Science and Technology, Kumamoto University
2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan

**Graduate School of Science and Technology, Kumamoto University
2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan

Received:
March 30, 2023
Accepted:
August 2, 2023
Published:
December 20, 2023
Keywords:
cooperative transport system, multi-robot, model error compensator, ideal formation
Abstract

In cooperative transport systems, multiple robots work together to transport objects that are difficult to transport with a single robot. In recent years, multi-robot systems that cooperate to transport objects have been researched. However, during the transfer of objects, misalignment occurs between the ideal and actual grasp positions. In an automatic transport system, a grasping error can cause an error in the trajectory of the object, significantly reducing the transport efficiency. In this paper, a control system that allows robust cooperative transport control using a model error compensator is proposed for a leader–follower system in which the transported object is the virtual leader and the followers are ideally arranged. This system adds robustness to the operation of a conventional cooperative transport system by using the ideal formation of robots. The effectiveness of the proposed method was evaluated through cooperative transport experiments using two ideal formations for passing through a narrow entrance. The cooperative transport system could not pass through the narrow entrance using the conventional method; however, the system using the compensator passed through the narrow entrance smoothly.

Robust cooperative transport control using multi-robots with an MEC

Robust cooperative transport control using multi-robots with an MEC

Cite this article as:
N. Matsunaga, K. Murata, and H. Okajima, “Robust Cooperative Transport System with Model Error Compensator Using Multiple Robots with Suction Cups,” J. Robot. Mechatron., Vol.35 No.6, pp. 1583-1592, 2023.
Data files:
References
  1. [1] A. Khamis, A. Hussein, and A. Elmogy, “Multi-robot task allocation: A review of the state-of-the-art,” Cooperative Robots and Sensor Networks, pp. 31-51, 2015. https://doi.org/10.1007/978-3-319-18299-5_2
  2. [2] E. Tuci, M. H. M. Alkilabi, and O. Akanyeti, “Cooperative object transport in multi-robot systems: A review of the state-of-the-art,” Frontiers in Robotics and AI, Vol.5, 2018. https://doi.org/10.3389/frobt.2018.00059
  3. [3] Y. Le, H. Kojima, and K. Matsuda, “Cooperative obstacle-avoidance pushing transportation of a planar object with one leader and two follower mobile robots,” J. Robot. Mechatron., Vol.17, No.1, pp. 78-88, 2005. https://doi.org/10.20965/jrm.2005.p0077
  4. [4] Y. Hirata, K. Kosuge, H. Asama, H. Kaetsu, and K. Kawabata, “Coordinated transportation of a single object by multiple mobile robots without position information of each robot,” Proc. of Int. Conf. on Intelligent Robots and Systems, pp. 2024-2029, 2000. https://doi.org/10.1109/IROS.2000.895268
  5. [5] W. Wan, R. Fukui, M. Shimosaka, T. Sato, and Y. Kuniyoshi, “Grasping by caging: A promising tool to deal with uncertainty,” Proc. of IEEE Int. Conf. on Robotics and Automation, pp. 5142-5149, 2012. https://doi.org/10.1109/ICRA.2012.6224676
  6. [6] X. Li, X. Liu, G. Wang, S. Han, C. Shi, and H. Che, “Cooperative target enclosing and tracking control with obstacles avoidance for multiple nonholonomic mobile robots,” Applied Science, Vol.12, No.6, Artilce No.2876, 2022. https://doi.org/10.3390/app12062876
  7. [7] D. Wang, W. Wei, X. Wang, Y. Gao, Y. Li, Q. Yu, and Z. Fan, “Formation control of multiple mecanum-wheeled mobile robots with physical constraints and uncertainties,” Applied Intelligence, Vol.52, pp. 2510-2529, 2021. https://doi.org/10.1007/s10489-021-02459-3
  8. [8] E. Abbasi, M. Ghayour, and M. Danesh, “Virtual leader-follower formation control of multi quadrotors by using feedback linearization controller,” Proc. of 5th RSI Int. Conf. on Robotics and Mechatronics, 2017. https://doi.org/10.1109/ICRoM.2017.8466165
  9. [9] N. Xuan-Mung and S. K. Hong, “Robust adaptive formation control of quadcopters based on a leader follower approach,” Int. J. of Advanced Robotic Systems, Vol.16, Issue 4, 2019. https://doi.org/10.1177/1729881419862733
  10. [10] X. Chen and Y. Jia, “Adaptive leader-follower formation control of non-holonomic mobile robots using active vision,” IET Control Theory and Applications, Vol.9, No.8, 2015. https://doi.org/10.1049/iet-cta.2014.0019
  11. [11] D. Koung, O. Kermorgant, I. Fantoni, and L. Belouaer, “Cooperative Multi-Robot Object Transportation System Based on Hierarchical Quadratic Programming,” IEEE Robotics and Automation Letters, Vol.6, Issue 4, pp. 6466-6472, 2021. https://doi.org/10.1109/LRA.2021.3092305
  12. [12] Z. Wang and M. Schwager, “Kinematic multi-robot manipulation with no communication using force feedback,” Proc. of the IEEE Int. Conf. on Robotics and Automation, pp. 427-432, 2016. https://doi.org/10.1109/ICRA.2016.7487163
  13. [13] Z. Wang, G. Yang, X. Su, and M. Schwager, “Ouijabots: Omnidirectional robots for cooperative object transport with rotation control using no communication,” Proc. of the Int. Symposium of Distributed Autonomous Robotic Systems (DARS), pp. 1-10, 2018. https://doi.org/10.1007/978-3-319-73008-0_9
  14. [14] L. Zhang, Y. Sun, A. Barth, and O. Ma, “Decentralized control of multirobot system in cooperative object transportation using deep reinforcement learning,” IEEE Access, Vol.8, pp. 184109-184119, 2020. https://doi.org/10.1109/ACCESS.2020.3025287
  15. [15] J. Orr and A. Dutta, “Multi-agent deep reinforcement learning for multi-robot applications: A survey,” Sensors, Vol.23, No.7, Article No.3625, 2023. https://doi.org/10.3390/s23073625
  16. [16] K. Murata, K. Miyazaki, and N. Matsunaga, “Experiment of cooperative transportation using multi-robots by multi-agent deep deterministic policy gradient,” Proc. of The 13th Asian Conf., 2022. https://doi.org/10.23919/ASCC56756.2022.9828156
  17. [17] A. Budiyanto and N. Matsunaga, “Deep Dyna-Q for rapid learning and improved formation achievement in cooperative transportation,” Automation, Vol.4, No.3, pp. 210-231, 2023. https://doi.org/10.3390/automation4030013
  18. [18] H. Okajima, H. Umei, N. Matsunaga, and T. Asai, “A design method of compensator to minimize model error,” SICE J. of Control Measurement and System Integration, Vol.6, No.4, pp. 267-275, 2013. https://doi.org/10.9746/jcmsi.6.267
  19. [19] H. Okajima, “Model error compensator for adding robustness toward existing control systems,” The 22nd IFAC World Congress 2023, pp. 3998-4005, 2023.
  20. [20] R. Yoshida, Y. Tanigawa, H. Okajima, and N. Matsunaga, “A design method of model error compensator for systems with polytopic-type uncertainty and disturbances,” SICE J. of Control, Measurement and System Integration, Vol.14, Issue 2, pp. 119-127, 2021. https://doi.org/10.1080/18824889.2021.1918392
  21. [21] T. Sugano, Y. Dan, H. Okajima, N. Matsunaga, and Z. Hu, “Indoor platoon driving of electric wheelchair with model error compensator along wheel track of preceding vehicle,” Proc. of 2014 Int. Conf. on Advanced Mechatronic Systems, 2014. https://doi.org/10.1109/ICAMechS.2014.6911565
  22. [22] H. Endo, R. Aramaki, K. Sekiguchi, and K. Nonaka, “Application of model error compensator based on FRIT to quadcopter,” 2017 IEEE Int. Conf. on Control Technology and Applications, 2017. https://doi.org/10.1109/CCTA.2017.8062761
  23. [23] L. Joseph and J. Cacace, “Mastering ROS for robotics programming: Best practices and troubleshooting solutions when working with ROS,” 3rd Edition, Packt Publishing, 2021.
  24. [24] E. Eros, M. Dahl, K. Bengtsson, A. Hanna, and P. Falkman, “A ROS2 based communication architecture for control in collaborative and intelligent automation systems,” Procedia Manufacturing, Vol.38, pp. 349-357, 2019. https://doi.org/10.1016/j.promfg.2020.01.045
  25. [25] A. K. Jaiswal and B. Kumar, “Vacuum cup grippers for material handling in industry,” Int. J. of Innovative Science, Engineering & Technology, Vol.4 Issue 6, pp. 187-194, 2017.
  26. [26] S. Ishida and H. Miyamoto, “Holonomic omnidirectional vehicle with ball wheel drive mechanism,” Trans. of the Japan Society of Mechanical Engineers, Series C, Vol.78, No.790, pp. 2162-2170, 2012 (in Japanese). https://doi.org/10.1299/kikaic.78.2162

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