Obstacle and Collision Avoidance Control Laws of a Swarm of Boids
This paper proposes a new obstacle and collision avoidance control laws for a three-dimensional swarm of boids. The swarm exhibit collective emergent behaviors whilst avoiding the obstacles in the workspace. While ﬂocking, animals group up in order to do various tasks and even a greater chance of evading predators. A generalized algorithms for attraction to the centroid, inter-individual swarm avoidance and obstacle avoidance is designed in this paper. We present a set of new continuous time-invariant velocity control laws is presented which is formulated via the Lyapunov-based control scheme. The control laws proposed in this paper also ensures practical stability of the system. The effectiveness of the proposed control laws is demonstrated via computer simulations
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1336999Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2119
 C. Blum and D. Merkle. Swarm Intelligence: Introduction and Applications. Springer - Verlag Berlin Heidelberg, Germany, 2008.
 M. Dorigo, L.M. Gambardella, M. Birattari, A. Martinoli, R. Poli, and T. Stützle. Ant Colony Optimization and Swarm Intelligence: 5th International Workshop, ANTS 2006, Brussels, Belgium, September 4-7, 2006, Proceedings, volume 4150. Springer, 2006.
 Q.K. Pan, M. Fatih Tasgetiren, and Y.C. Liang. A discrete particle swarm optimization algorithm for the no-wait ﬂowshop scheduling problem. Computers & Operations Research, 35(9):2807–2839, 2008.
 G.J. Gelderblom, G. Cremers, M. de Wilt, W. Kortekaas, A. Thielmann, K. Cuhls, A. Sachinopoulou, and I. Korhonen. The opinions expressed in this study are those of the authors and do not necessarily reﬂect the views of the european commission. 2008.
 B. Sharma, J. Vanualailai, and S. Singh. Tunnel passing maneuvers of prescribed formations. International Journal of Robust and Nonlinear Control, 2012.
 B. Sharma, J. Vanualailai, and S. Singh. Lyapunov-based nonlinear controllers for obstacle avoidance with a planar -link doubly nonholonomic manipulator. Robotics and Autonomous Systems, 2012.
 B. Sharma, J. Vanualailai, and U. Chand. Flocking of multi-agents in constrained environments. European Journal of Pure and Applied Mathematics, 2(3):401–425, 2009.
 B. Sharma. New Directions in the Applications of the Lyapunov-based Control Scheme to the Findpath Problem. PhD thesis, University of the South Paciﬁc, Suva, Fiji Islands, July 2008. PhD Dissertation.
 O. Lefebvre, F. Lamiraux, and C. Pradalier. Obstacles avoidance for car-like robots: Integration and experimentation on two robots. In IEEE International Conference on Robotics and Automation, New Orleans, April 26th - May 1st 2004.
 V. Lakshmikantham, S. Leela, and A. A. Martynyuk. Practical Stability of Nonlinear Systems. World Scientiﬁc, Singapore, 1990.
 C. W. Reynolds. Flocks, herds, and schools: A distributed behavioral model, in computer graphics. In Proceedings of the 14th annual conference on Computer graphics and interactive techniques, pages 25–34, New York, USA, 1987.
 A. Ordemann, G. Balazsi, and F. Moss. Pattern formation and stochastic motion of the zooplankton Daphina in a light ﬁeld. Physica A, 325:260–266, 2003.
 F. Moss. Into the Daphina vortex. Chaos, 14(4):S10, 2004.
 M. T. Butler, Q. Wang, and R. M Harshy. Cell density and mobility protect swarming bacteria against antibiotics. Proceedings of the National Academy of Sciences, 107(8):3776–3781, 2010.
 P. C-Y. Sheu and Q. Xue. Intelligent Robotic Planning Systems. World Scientiﬁc, Singapore, 1993.