Special Issue on Selected Papers from the 17th Annual IEEE International Conference (ICTAI-2005); Guest Editors: Fan Wang and Andrew LimNo Access

APPLYING A TAXONOMY OF FORMATION CONTROL IN DEVELOPING A ROBOTIC SYSTEM

HARRY CHIA-HUNG HSU

Department of Electrical Engineering, National Chung Cheng University, Taiwan

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and

ALAN LIU

Department of Electrical Engineering and Center for Telecommunication Research, National Chung Cheng University, Taiwan

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https://doi.org/10.1142/S0218213007003436Cited by:1 (Source: Crossref)

Abstract

Designing cooperative multi-robot systems (MRS) requires expert knowledge both in control and artificial intelligence. Formation control is an important research within the research field of MRS. Since many researchers use different ways in approaching formation control, we try to give a taxonomy in order to help researchers design formation systems in a systematical way. We can analyze formation structures in two categories: control abstraction and robot distinguishability. The control abstraction can be divided into three layers: formation shape, reference type, and robotic control. Furthermore, robots can be classified as anonymous robots or identification robots depending on whether robots are distinguishable according to their inner states. We use this taxonomy to analyze some ground-based formation systems and to state current challenges of formation control. Such information becomes the design know-how in developing a formation system, and a case study of designing a multi-team formation system is introduced to demonstrate the usefulness of the taxonomy.

This research was supported in part by the Ministry of Education under grant EX-91-E-FA06-4-4 and the National Science Council under grant NSC-93-2213-E-194-039.

Keywords:

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References

Y. U. Cao, A. S. Fukunaga and A. B. Kahng, Autonomous Robots 4, 1 (1997), DOI: 10.1023/A:1008855018923. Google Scholar
T. Arai, E. Pagello and L. E. Parker, IEEE Transaction on Robotics and Automation 18(5), 655 (2002), DOI: 10.1109/TRA.2002.806024. Crossref, Google Scholar
P. Stone and M. Veloso, Artificial Intelligence 110(2), 241 (1999), DOI: 10.1016/S0004-3702(99)00025-9. Crossref, Web of Science, Google Scholar
T. Balch and R. C. Arkin, IEEE Transactions on Robotics and Automation 14(6), 926 (1998), DOI: 10.1109/70.736776. Crossref, Google Scholar
T. Balch and M. Hybinette , Social potentials for scalable multi-robot formations , IEEE International Conference on Robotics and Automation (ICRA) ( 2000 ) . Google Scholar
H. C.-H. Hsu and A. Liu, Journal of Intelligent and Robotic Systems 42(4), 337 (2005), DOI: 10.1007/s10846-005-2965-7. Crossref, Web of Science, Google Scholar
A. K. Daset al., IEEE Transaction on Robotics and Automation 18(5), 813 (2002), DOI: 10.1109/TRA.2002.803463. Crossref, Google Scholar
J. P. Desai, Journal of Robtic Systems 19(11), 511 (2002), DOI: 10.1002/rob.10057. Crossref, Web of Science, Google Scholar
M. A. Lewis and K.-H. Tan, Autonomous Robots 4(4), 387 (1997), DOI: 10.1023/A:1008814708459. Crossref, Web of Science, Google Scholar
K. Sugihara and I. Suzuki, Journal of Robotic Systems 13(3), 127 (1996). Crossref, Google Scholar
R. C. Arkin, Behavior-Based Robotics (MIT Press, 1998) p. 361. Google Scholar
C. W. Reynolds, Computer Graphics 21(4), 25 (1987), DOI: 10.1145/37402.37406. Crossref, Google Scholar
M. J. Mataric, Adaptive Behavior 4(1), 50 (1995), DOI: 10.1177/105971239500400104. Google Scholar
G. Dudeket al., Autonomous Robots 3, 375 (1996), DOI: 10.1007/BF00240651. Web of Science, Google Scholar
T. Balch and L. E. Parker (eds.) , Robot Teams: From Diversity to Polymorphism ( AK Peters , 2002 ) . Crossref, Google Scholar
M. Wooldridge , An Introduction to Multiagent Systems ( Wiley Press , 2002 ) . Google Scholar
D. V. Pynadath and M. Tambe, Autonomous Agents and Multi-Agent Systems 7(1-2), 71 (2003), DOI: 10.1023/A:1024176820874. Crossref, Web of Science, Google Scholar
V. Lesseret al., Autonomous Agents and Multi-Agent Systems 9(1/2), 87 (2004), DOI: 10.1023/B:AGNT.0000019690.28073.04. Crossref, Web of Science, Google Scholar
X. Yun, G. Alptekin and O. Albayrak, Journal of Robotic Systems 14(2), 63 (1997). Crossref, Google Scholar
M. Egerstedt and X. Hu, IEEE Transactions on Robotics and Automation 17(6), (2001), DOI: 10.1109/70.976029. Google Scholar
J. Fredslund and M. J. Mataric, IEEE Transaction on Robotics and Automation 18(5), 837 (2002), DOI: 10.1109/TRA.2002.803458. Crossref, Google Scholar
T. D. Barfoot and C. M. Clark, Robotics and Autonomous Systems 46, 65 (2004), DOI: 10.1016/j.robot.2003.11.004. Crossref, Web of Science, Google Scholar
S. S. Ge and C.-H. Fua, IEEE Transactions on Robotics 21(4), 646 (2005), DOI: 10.1109/TRO.2005.847617. Crossref, Web of Science, Google Scholar
D. Swaroop and J. K. Hedrick, IEEE Transactions on Automatic Control 41(3), 349 (1996), DOI: 10.1109/9.486636. Crossref, Web of Science, Google Scholar
A. Pant, P. Seiler and K. Hedrick, IEEE Transactions on Automatic Control 47(2), 403 (2002), DOI: 10.1109/9.983389. Crossref, Web of Science, Google Scholar
H. G. Tanner, G. J. Pappas and V. Kumar, IEEE Transactions on Robotics and Automation 20(3), 443 (2004), DOI: 10.1109/TRA.2004.825275. Crossref, Google Scholar
F. Giulietti, L. Pollini and M. Innocenti, IEEE Control Systems Magazine 20(6), 34 (2000). Crossref, Web of Science, Google Scholar