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
[1] C. Blum and D. Merkle. Swarm Intelligence: Introduction and
Applications. Springer - Verlag Berlin Heidelberg, Germany, 2008.
[2] 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.
[3] 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.
[4] 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.
[5] B. Sharma, J. Vanualailai, and S. Singh. Tunnel passing maneuvers of
prescribed formations. International Journal of Robust and Nonlinear
Control, 2012.
[6] 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.
[7] 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.
[8] 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.
[9] 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.
[10] V. Lakshmikantham, S. Leela, and A. A. Martynyuk. Practical Stability
of Nonlinear Systems. World Scientific, Singapore, 1990.
[11] 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.
[12] 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.
[13] F. Moss. Into the Daphina vortex. Chaos, 14(4):S10, 2004.
[14] 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.
[15] P. C-Y. Sheu and Q. Xue. Intelligent Robotic Planning Systems. World
Scientific, Singapore, 1993.
[1] C. Blum and D. Merkle. Swarm Intelligence: Introduction and
Applications. Springer - Verlag Berlin Heidelberg, Germany, 2008.
[2] 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.
[3] 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.
[4] 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.
[5] B. Sharma, J. Vanualailai, and S. Singh. Tunnel passing maneuvers of
prescribed formations. International Journal of Robust and Nonlinear
Control, 2012.
[6] 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.
[7] 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.
[8] 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.
[9] 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.
[10] V. Lakshmikantham, S. Leela, and A. A. Martynyuk. Practical Stability
of Nonlinear Systems. World Scientific, Singapore, 1990.
[11] 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.
[12] 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.
[13] F. Moss. Into the Daphina vortex. Chaos, 14(4):S10, 2004.
[14] 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.
[15] P. C-Y. Sheu and Q. Xue. Intelligent Robotic Planning Systems. World
Scientific, Singapore, 1993.
@article{"International Journal of Engineering, Mathematical and Physical Sciences:66354", author = "Bibhya Sharma and Jito Vanualailai and Jai Raj", title = "Obstacle and Collision Avoidance Control Laws of a Swarm of Boids", abstract = "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
", keywords = "Lyapunov-based Control Scheme, Motion planning,
Practical stability, Swarm.", volume = "8", number = "2", pages = "272-6", }