Distributed, physics-based control of swarms of vehicles

Autonomous Robots

Volumn 17, Issue 2-3, 2004, Pages 137-162

  Spears, William M ^a   Spears, Diana F ^a   Hamann, Jerry C ^b   Heil, Rodney ^b  

^a UNIVERSITY OF WYOMING   (United States)

^b UNIVERSITY OF WYOMING   (United States)

Author keywords

Fault tolerance; Formations; Physicomimetics; Predictability; Self organization; Swarm robotics

Indexed keywords

FAULT-TOLERANCE; FORMATIONS; PHYSICOMIMETICS; PREDICTABILITY; SELF-ORGANIZATION; SWARM ROBOTICS; SWARMS;

ALGORITHMS; AUTOMATION; COSTS; DISTRIBUTED PARAMETER CONTROL SYSTEMS; FAULT TOLERANT COMPUTER SYSTEMS; FRICTION; MOBILE ROBOTS; MULTI AGENT SYSTEMS; NETWORKS (CIRCUITS); POTENTIAL ENERGY; ROBUSTNESS (CONTROL SYSTEMS); VISCOSITY;

ROBOTICS;

EID: 3142697699     PISSN: 09295593     EISSN: None     Source Type: Journal    
DOI: 10.1023/B:AURO.0000033970.96785.f2     Document Type: Article

References (51)

1. Alur, R., Esposito, J., Kim, M., Kumar, J., and Lee, I. 1999. Formal modeling and analysis of hybrid systems: A case study in multi-robot coordination. Lecture Notes in Computer Science, 1708:212-232.
2. Balch, T. and Arkin, R. 1998. Behavior-based formation control for multi-robot teams. IEEE Transactions on Robotics and Automata, 14(6):1-15.
3. Beni, G. and Hackwood, S. 1992. Stationary waves in cyclic swarms. Intelligent Control, 234-242.
4. Beni, G. and Wang, J. 1989. Swarm intelligence. In Proceedings of the Seventh Annual Meeting of the Robotics Society of Japan, Tokyo, Japan, pp. 425-428.
5. Bonabeau, E., Dorigo, M., and Theraulaz, G. 1999. Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press: Santa Fe Institute Studies in the Sciences of Complexity, Oxford, NY.
6. Brogan, D. and Hodgins, J. 1997, Group behaviors for systems with significant dynamics. Autonomous Robots, 4:137-153.
7. Carlson, B., Gupta, V., and Hogg, T. 1997. Controlling agents in smart matter with global constraints. In AAAI-97 Workshop on Constraints and Agents - Technical Report WS-97-05, E.C. Freuder (Ed.).
8. Czirok, A., Vicsek, M., and Vicsek, T. 1999. Collective motion of organisms in three dimensions. Physica A, 264(299):299-304.
9. Desai, J., Ostrowski, J., and Kumar, V. 2001, Modeling and control of formations of nonholonomic mobile robots, IEEE Transactions on Robotics and Automation, 17(6):905-908.
10. Desai, J., Ostrowski, J., and Kumar, V. 1998. Controlling formations of multiple mobile robots. In IEEE International Conference on Robotics and Automation, Belgium, pp. 2864-2869.
11. Fax, J. and Murray, R. 2002. Information flow and cooperative control of vehicle formations. In IFAC World Congress, Barcelona, Spain.
12. Fernandez, F. and Parker, L. 2002. Learning in large cooperative multi-robot domains. International Journal of Robotics and Automation, 16(4):217-226.
13. Fierro, R., Belta, C., Desai, J., and Kumar, V. 2001. On controlling aircraft formations, In IEEE Conference on Decision and Control, vol. 2, Orlando, Florida, pp. 1065-1070.
14. Fierro, R., Song, P., Das, A., and Kumar, V. 2002, Cooperative control of robot formations. In Cooperative Control and Optimization, R. Murphey and P. Pardalos (Eds.), vol. 66, Kluwer Academic Press: Hingham, MA, pp. 73-93.
15. Fredslund, J. and Matarić, M. 2002. A general algorithm for robot formations using local sensing and minimal communication. IEEE Transactions on Robotics and Automation, 18(5):837-846.
16. Goldberg, D. and Matarić, M. 2000. Learning multiple models for reward maximization. In Seventeenth International Conference on Machine Learning, Stanford, CA, pp. 319-326.
17. Goldberg, D.E. 1989. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley.
18. Gordon, D., Spears, W., Sokolsky, O., and Lee, I. 1999. Distributed spatial control, global monitoring and steering of mobile physical agents. In IEEE International Conference on Information, Intelligence, and Systems, Washington, DC, pp. 681-688.
19. Gordon-Spears, D. and Spears, W. 2003. Analysis of a phase transition in a physics-based multiagent system. In Lecture Notes in Computer Science, M. Hinchey, J. Rash, W. Truszkowski, C. Rouff, and D. Gordon-Spears (Eds.), vol. 2699, Springer-Verlag: Greenbelt, MD, pp. 193-207.
20. Hayes, A., Martinoli, A., and Goodman, R. 2002. Distributed odor source localization. IEEE Sensors, 2(3):260-271.
21. Helbing, D., Farkas, I., and Vicsek, T. 2000. Simulating dynamical features of escape panic. Nature, 407:487-490.
22. Holland, J. 1975. Adaptation in Natural and Artificial Systems. University of Michigan Press: Michigan, USA.
23. Howard, A., Matarić, M., and Sukhatme, G. 2002. Mobile sensor network deployment using potential fields: A distributed, scalable solution to the area coverage problem. In Sixth International Symposium on Distributed Autonomous Robotics Systems, ACM: Fukuoka, Japan, pp. 299-308.
24. Jantz, S., Doty, K., Bagnell, I., and Zapata, I. 1997. Kinetics of robotics: The development of universal metrics in robotic swarms. In Florida Conference on Recent Advances in Robotics, Miami, Florida.
25. Kellogg, J., Bovais, C., Foch, R., McFarlane, H., Sullivan, C., Dahlburg, J., Gardner, J., Ramamurti, R., Gordon-Spears, D., Hartley, R., Kamgar-Parsi, B., Pipitone, F., Spears, W., Sciambi, A., and Srull, D. 2002. The NRL micro tactical expendable (MITE) air vehicle. The Aeronautical Journal, 106(1062):431-441.
26. Khatib, O. 1986. Real-time obstacle avoidance for manipulators and mobile robots. International Journal of Robotics Research, 5(1):90-98.
27. Kraus, S., Shehory, O., and Yadgar, O. 1999. Emergent cooperative goal-satisfaction in large-scale automated-agent systems. Artificial Intelligence, 110:1-55.
28. Navarro-Serment, L.L., Paredis, C., and Khosla, P. 1999. A beacon system for the localization of distributed robotic teams. In International Conference on Field and Service Robots, Pittsburgh, PA, pp. 232-237.
29. Lerman, K. and Galstyan, A. 2001. A general methodology for mathematical analysis of multi-agent systems. Technical Report ISI-TR-529, USC Information Sciences.
30. Liu, Y., Passino, K., and Polycarpou, M. 2003. Stability analysis of m-dimensional asynchronous swarms with a fixed communication topology. IEEE Transactions on Automatic Control, 48:76-95.
31. Matarić, M. 1995. Designing and understanding adaptive group behavior. Technical report, CS Dept., Brandeis Univ.
32. Numaoka, C. 1995. Phase transitions in instigated collective decision making. Adaptive Behavior, 3(2):185-222.
33. Olfati-Saber, R. and Murray, R. 2002. Distributed cooperative control of multiple vehicle formations using structural potential functions. In IFAC World Congress, Barcelona, Spain.
34. Parker, L. 1998. Alliance: An architecture for fault tolerant multirobot cooperation. IEEE Transactions on Robotics and Automation, 14(2):220-240.
35. Parker, L. 1998. Toward the automated synthesis of cooperative mobile robot teams. In SPIE Mobile Robots XIII, vol. 3525, Boston, MA, pp. 82-93.
36. Potter, M., Meeden, L., and Schultz, A. 2001. Heterogeneity in the coevolved behaviors of mobile robots: The emergence of specialists. In Seventh International Conference on Artificial Intelligence, Morgan Kaufmann: Seattle, Washington, pp. 1337-1343.
37. Reif, J. and Wang, H. 1999. Social potential fields: A distributed behavioral control for autonomous robots. In Robotics and Autonomous Systems, 27(3):171-194.
38. Reynolds, C. 1987. Flocks, herds, and schools: A distributed behavioral model. In Proceedings of SIGGRAPH'87, vol. 21, no. 4, ACM Computer Graphics: New York, NY, pp. 25-34.
39. Schoenwald, D., Feddema, J., and Oppel, F. 2001. Decentralized control of a collective of autonomous robotic vehicles. In American Control Conference, Arlington, VA, pp. 2087-2092.
40. Schultz, A., Grefenstette, J., and Adams, W. 1996. Roboshepherd: Learning a complex behavior. In Robotics and Manufacturing: Recent Trends in Research and Applications, vol. 6, ASME Press: New York, pp. 763-768.
41. Schultz, A. and Parker, L. (Eds.). 2002. Multi-Robot Systems: From Swarms to Intelligent Automata, Kluwer: Hingham, MA.
42. Simmons, R., Smith, T., Dias, M., Goldberg, D., Hershberger, D., Stentz, A., and Zlot, R. 2002. A layered architecture for coordination of mobile robots. In Multi-Agent Robot Systems: From Swarms to Intelligent Automata, A. Schultz and L. Parker (Eds.), Kluwer: Hingham, MA.
43. Slack, M. 1990. Situationally driven local navigation for mobile robots, PhD thesis, Virginia Polytechnic.
44. Spears, W., De Jong, K., Bäck, T., Fogel, D., and Garis de, H. 1993. An overview of evolutionary computation. In European Conference on Machine Learning, vol. 667, Springer Verlag: Austria, pp. 442-459.
45. Spears, W. and Gordon, D. 1999. Using artificial physics to control agents. In IEEE International Conference on Information, Intelligence, and Systems, Washington, DC, pp. 281-288.
46. Suzuki, I. and Yamashita, M. 1999. Distributed anonymous mobile robots: Formation of geometric patterns. SIAM Journal of Computation, 28(4):1347-1363.
47. Toner, J. and Tu, Y. 1998. Flocks, herds, and schools: A quantitative theory of flocking. Physical Review E, 58(4):4828-4858.
48. Tu, X. and Terzopoulos, D. 1994. Artifical fishes: Physics, locomotion, perception, behavior. In. Proceedings of SIGGRAPH'94, ACM Computer Graphics: Orlando, Florida, pp. 43-50.
49. Vail, D. and Veloso, M. 2003. Multi-robot dynamic role assignment and coordination through shared potential fields. In Multi-Robot Systems, A. Schultz, L. Parker, and F. Schneider (Eds.), Kluwer: Hingham, MA, pp. 87-98.
50. Vicsek, T., Czirok, A., Ben-Jacob, E., Cohen, I., and Shocher, O. 1995. Novel type of phase transition in a system of self-driven particles. Physics Review Letters, 75(6):1226-1229.
51. Wu, A., Schultz, A., and Agah, A. 1999. Evolving control for distributed micro air vehicles. In IEEE Conference on Computational Intelligence in Robotics and Automation, Belgium, pp. 174-179.