Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-25T02:22:08.840Z Has data issue: false hasContentIssue false
  • English
  • Français

Cooperative object transportation using parallel line formation with a circular shift

Published online by Cambridge University Press:  04 March 2016

Gyuho Eoh ,
Jae D. Jeon ,
Jung H. Oh  and
Beom H. Lee
Gyuho Eoh*
Affiliation:
Seoul National University (Department of Electrical and Computer Engineering)
Jae D. Jeon
Affiliation:
Seoul National University (Department of Electrical and Computer Engineering)
Jung H. Oh
Affiliation:
Seoul National University (Department of Electrical and Computer Engineering)
Beom H. Lee
Affiliation:
Seoul National University (Department of Electrical and Computer Engineering)
*
*Corresponding author. E-mail: [email protected], [email protected], [email protected], [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

This paper presents a new cooperative object transportation technique using parallel line formation with a circular shift. Typical areas of research in relation to object transportation are grasping, pushing, and caging techniques, but these require precise grasping behaviors, iterative motion correction according to the object pose, and the real-time acquisition of the object shape, respectively. In this paper, the proposed technique does not need to consider the shape or the pose of objects, and equipped tools are not necessary for object transportation because objects are transported by pushing behavior only. Multiple robots create parallel line formation using a virtual electric dipole field and then push multiple objects into the formation. This parallel line is extended to the goal using cyclic motion by the robots and the objects are transported to the goal by pushing behavior. The above processes are decentralized and activated based on the finite state machine of each robot. Simulations and practical experiments are presented to verify the proposed technique.

Keywords

Cooperative object transportationCircular shiftFinite state machineElectric dipole field
Type
Articles
Information
Robotica , Volume 35 , Issue 6 , June 2017 , pp. 1341 - 1364
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Arai, T., Pagello, E. and Parker, L. E., “Guest editorial: Advances in multirobot systems,” IEEE Trans. Robot. Autom. 18 (5), 655–661 (2002).Google Scholar
2. Cao, Y. U., Fukunaga, A. S. and Kahng, A., “Cooperative mobile robotics: Antecedents and directions,” Auton. Robots. 4 (1), 7–27 (1997).Google Scholar
3. Spletzer, J., Das, A. K., Fierro, R., Taylor, C. J., Kumar, V. and Ostrowski, J. P., “Cooperative Localization and Control for Multi-Robot Manipulation,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Maui, HI (2001) pp. 631–636.Google Scholar
4. Ahmadabadi, M. N. and Nakano, E., “A “constrain and move” approach to distributed object manipulation,” IEEE Trans. Robot. Autom. 17 (2), 157–172 (2001).CrossRefGoogle Scholar
5. Shinde, V., Dutta, A. and Saxena, A., “Experiments on multi-agent capture of a stochastically moving object using modified projective path planning,” Robotica 31 (2), 267–284 (2013).Google Scholar
6. Bicchi, A., “On the closure properties of robotic grasping,” Int. J. Robot. Res. 14 (4), 319–334 (1999).Google Scholar
7. Liu, Y. H., “Qualitative test and force optimization of 3d frictional form-closure grasps using linear programming,” IEEE Trans. Robot. Autom. 15 (1), 163–173 (1999).Google Scholar
8. Liu, Z., Kamogawa, H. and Ota, J., “Fast grasping of unknown objects through automatic determination of the required number of mobile robots,” Adv. Robotics 27 (6), 445–458 (2013).Google Scholar
9. Groß, R., Tuci, E., Dorigo, M., Bonani, M. and Mondada, F., “Object Transport by Modular Robots that Self-Assemble,” Proceedings of IEEE International Conference on Robotics and Automation, Los Alamitos, CA (2006) pp. 2558–2564.Google Scholar
10. Mataric, M. J., Nilsson, M. and Simsarian, K. T., “Cooperative Multi-Robot Box-Pushing,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Pittsburgh, PA (1995) pp. 556–561.Google Scholar
11. Li, Q. and Payandeh, S., “Manipulation of convex objects via two-agent point-contact push,” Int. J. Robot. Res. 26 (4), 377–403 (2007).Google Scholar
12. Gerkey, B. P. and Matarić, M. J., “Sold!: Auction methods for multi-robot coordination,” IEEE Trans. Robot. Autom. 18 (5), 758–768 (2002).Google Scholar
13. Eoh, G., Choi, J. S. and Lee, B. H., “Faulty robot rescue by multi-robot cooperation,” Robotica 31 (8), 1239–1249 (2013).Google Scholar
14. Pereira, G. A. S., Campos, M. F. M. and Kumar, V., “Decentralized algorithms for multi-robot manipulation via caging,” Int. J. Robot. Res. 23 (7–8), 783–795 (2004).Google Scholar
15. Wan, W., Fukui, R., Shimosaka, M., Sato, T. and Kuniyoshi, Y., “Grasping by Caging: A Promising Tool to Deal with Uncertainty,” Proceedings of IEEE International Conference on Robotics and Automation, Saint Paul, MN (2012) pp. 5142–5149.Google Scholar
16. Donald, B., Gariepy, L. and Rus, D., “Distributed Manipulation of Multiple Objects using Ropes,” Proceedings of the IEEE International Conference on Robotics and Automation, San Francisco, CA (2000) pp. 450–457.Google Scholar
17. Fink, J., Cheng, P. and Kumar, V., “Cooperative Towing with Multiple Robots,” Proceedings of the ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, New York, USA (2008) pp. 1269–1276.Google Scholar
18. Eoh, G., Lee, K. W., Oh, J. H., Lee, S. H. and Lee, B. H., “Cooperative multiple-object towing with linked robots,” J. Commun. Comput. 10 (3), 385–393 (2013).Google Scholar
19. Yamashita, A., Arai, T., Ota, J. and Asama, H., “Motion planning of multiple mobile robots for cooperative manipulation and transportation,” IEEE Trans. Robot. Autom. 19 (2), 223–237 (2003).Google Scholar
20. Eoh, G., Cho, Y. and Lee, B. H., “Reconfigurable Formation Control for Multi-object Transportation,” Proceedings of the 12th International Conference on Distributed Autonomous Robotic Systems, Daejeon, South Korea (2014) pp. 304–305.Google Scholar
21. Ren, J., McIsaac, K. A. and Patel, R. V., “A potential model using generalized sigmoid functions,” IEEE Trans. Syst. Man Cybern. B. 37 (2), 477–484 (2007).CrossRefGoogle ScholarPubMed
22. Li, Z., Liu, G., Yang, Y. and You, J., “Scale- and rotation-invariant local binary pattern using scale-adaptive texton and subuniform-based circular shift,” IEEE Trans. Image Process. 21 (4), 2130–2140 (2012).Google Scholar
23. Cheng, D. K., Field and Wave Electromagnetics, 2nd ed. (Addison-Wesley, Reading, MA, 1989).Google Scholar
24. Igarashi, T., Kamiyama, Y. and Inami, M., “A Dipole Field for Object Delivery by Pushing on a Flat Surface,” Proceedings of the IEEE International Conference on Robotics and Automation, Anchorage, AK (2010) pp. 5149–5119.Google Scholar
25. Koh, K. C. and Cho, H. S., “A smooth path tracking algorithm for wheeled mobile robots with dynamic constraints,” J. Intell. Robot. Syst. 24 (4), 367–385 (1999).Google Scholar
26. Rubenstein, M., Cornejo, A. and Nagpal, R., “Programmable self-assembly in a thousand-robot swarm,” Science 345 (6198), 795–799 (2014).Google Scholar
27. Kim, D., Jeong, K. H. and Lee, B. H., “An approach to multi-agent interactive control in an intelligent space,” Int. J. Control, Autom. Syst. 13 (3), 697–708 (2015).Google Scholar