Buradasınız

Flocking of Multi-agents in Constrained Environments

Journal Name:

Publication Year:

Abstract (2. Language): 
Flocking, arguably one of the most fascinating concepts in nature, has in recent times established a growing stature within the field of robotics. In this paper, we control the collective motion of a flock of nonholonomic car-like vehicles in a constrained environment. A continuous centralized motion planner is proposed for split/rejoin maneuvers of the flock via the Lyapunov-based control scheme to anchor avoidance of obstacles intersecting the paths of flockmates. The control scheme inherently utilizes the artificial potential fields, within a new leader-follower framework, to accomplish the desired formations and reformations of the flock. The effectiveness of the proposed control laws are demonstrated through computer simulations.
401-425

REFERENCES

References: 

[1] C. Belta and V. Kumar. Abstraction and control for groups of robots. In Reprinted from
IEEE Transactions on Robotics and Automation, volume 4, pages 865–875, October 2004.
[2] R.W. Brockett. Differential Geometry Control Theory, chapter Asymptotic Stability and
Feedback Stabilisation, pages 181–191. Springer-Verlag, 1983.
[3] D. E. Chang, S. C. Shadden, J. E. Marsden, and R. Olfati-Saber. Collision avoidance for
multiple agent systems. In Procs. of the 42nd IEEE Conference on Decision and Control,
Maui, Hawaii USA, December 2003.
[4] D. Crombie. The examination and exploration of algorithms and complex behavior to
realistically control multiple mobile robots. Master’s thesis, Australian National University,
1997.
[5] P. ¨Ogren. Formations and obstacle avoidance in mobile robot control. Master’s thesis,
Royal Institute of Technology, Stockholm, Sweden, June 2003.
[6] L. Edelstein-Keshet. Mathematical models of swarming and social aggregation. In
Procs. 2001 International Symposium on Nonlinear Theory and Its Applications, pages
1–7, Miyagi, Japan, October-November 2001.
[7] G. H. Elkaim and R. J. Kelbley. A lightweight formation control methodology for a
swarm of non-holonomic vehicles. In IEEE Aerospace Conference, 2006.
[8] V. Gazi. Swarm aggregations using artificial potentials and sliding mode control. In
Procs. IEEE Conference on Decision and Control, pages 2041–2046, Maui, Hawaii, December
2003.
REFERENCES 425
[9] W. Kang, N. Xi, J. Tan, and Y. Wang. Formation control of multiple autonomous robots:
Theory and experimentation. Intelligent Automation and Soft Computing, 10(2):1–17,
2004.
[10] J-C. Latombe. Robot Motion Planning. Kluwer Academic Publishers, USA, 1991.
[11] M. Lindh´e. A flocking and obstacle avoidance algorithm for mobile robots. Master’s
thesis, KTH School of Electrical Engineering, Stockholm, Sweden, June 2004.
[12] C.W. Reynolds. Flocks, herds, and schools: A distributed behavioral model, in computer
graphics. In Procs. of the 14th annual conference on Computer graphics and interactive
techniques, pages 25–34, New York, USA, 1987.
[13] B. Sharma. New directions in the applications of the lyapunov-based control scheme to
the findpath problem. PhD Dissertation, July 2008.
[14] B. Sharma and J. Vanualailai. Lyapunov stability of a nonholonomic car-like robotic
system. Nonlinear Studies, 14(2):143–160, 2007.
[15] B. Sharma, J. Vanualailai, and A. Prasad. Formation control of a swarm of mobile
manipulators. Rocky Mountain Journal of Mathematics, To Appear.
[16] H. Tanner, A. Jadbabaie, and G. J. Pappas. Stable flocking of mobile agents, part i:
Fixed topology. In Procs. of the 42nd IEEE Conference on Decision and Control, pages
2010–2015, 2003.
[17] R. Olfati-Saber. Flocking for multi-agent dynamic systems: Algorithms and theory. IEEE
Transactions on Automatic Control, 51(3):401–420, 2006.
[18] R. Olfati-Saber and R. M. Murray. Flocking with obstacle avoidance: Cooperation with
limited information in mobile networks. In Procs. of the 42nd IEEE Conference on Deci-
sion and Control, volume 2, pages 2022–2028, Maui, Hawaii, December 2003.
[19] J. Vanualailai, B. Sharma, and A. Ali. Lyapunov-based kinematic path planning for a
3-link planar robot arm in a structured environment. Global Journal of Pure and Applied
Mathematics, 3(2):175–190, 2007.

Thank you for copying data from http://www.arastirmax.com