Abstract
A formation driving mechanism suited for utilization of multi-robot teams in highly dynamic environments is proposed in this paper. The presented approach enables to integrate a prediction of behaviour of moving objects in robots’ workspace into a formation stabilization and navigation framework. It will be shown that such an inclusion of a model of the surrounding environment directly into the formation control mechanisms facilitates avoidance manoeuvres in a case of fast dynamic objects approaching in a collision course. Besides, the proposed model predictive control based approach enables to stabilize robots in a compact formation and it provides a failure tolerance mechanism with an inter collision avoidance. The abilities of the algorithm are verified via numerous simulations and hardware experiments with the main focus on evaluation of performance of the algorithm with different sensing capabilities of the robotic system.
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Ghommam, J., Mehrjerdi, H., Saad, M., Mnif, F.: Formation path following control of unicycle-type mobile robots. Robotics and Autonomous Systems 58(5), 727–736 (2010)
Ren, W.: Decentralization of virtual structures in formation control of multiple vehicle systems via consensus strategies. European Journal of Control 14, 93–103 (2008)
Beard, R., Lawton, J., Hadaegh, F.: A coordination architecture for spacecraft formation control. IEEE Transactions on Control Systems Technology 9(6), 777–790 (2001)
Hengster-Movrić, K., Bogdan, S., Draganjac, I.: Multi-agent formation control based on bell-shaped potential functions. Journal of Intelligent and Robotic Systems 58(2) (2010)
Langer, D., Rosenblatt, J., Hebert, M.: A behavior-based system for off-road navigation. IEEE Transactions on Robotics and Automation 10(6), 776–783 (1994)
Lawton, J., Beard, R., Young, B.: A decentralized approach to formation maneuvers. IEEE Transactions on Robotics and Automation 19(6), 933–941 (2003)
Min, H.J., Papanikolopoulos, N.: Robot formations using a single camera and entropy-based segmentation. Journal of Intelligent and Robotic Systems (1), 1–21 (2012)
Chen, J., Sun, D., Yang, J., Chen, H.: Leader-follower formation control of multiple non-holonomic mobile robots incorporating a receding-horizon scheme. Int. Journal Robotic Research 29, 727–747 (2010)
Das, A., Fierro, R., Kumar, V., Ostrowski, J., Spletzer, J., Taylor, C.: A vision-based formation control framework. IEEE Transactions on Robotics and Automation 18(5), 813–825 (2003)
Dong, W.: Robust formation control of multiple wheeled mobile robots. Journal of Intelligent and Robotic Systems 62(3-4), 547–565 (2011)
Abdessameud, A., Tayebi, A.: Formation control of vtol unmanned aerial vehicles with communication delays. Automatica 47(11), 2383–2394 (2011)
Do, K.D., Lau, M.W.: Practical formation control of multiple unicycle-type mobile robots with limited sensing ranges. Journal of Intelligent and Robotic Systems 64(2), 245–275 (2011)
Xiao, F., Wang, L., Chen, J., Gao, J.: Finite-time formation control for multi-agent systems. Automatica 45(11), 2605–2611 (2009)
Boscariol, P., Gasparetto, A., Zanotto, V.: Model predictive control of a flexible links mechanism. Journal of Intelligent and Robotic Systems 58(2), 125–147 (2010)
Chao, Z., Zhou, S.L., Ming, L., Zhang, W.G.: Uav formation flight based on nonlinear model predictive control. Mathematical Problems in Engineering 2012(1), 1–16 (2012)
Zhang, X., Duan, H., Yu, Y.: Receding horizon control for multi-uavs close formation control based on differential evolution. Science China Information Sciences 53, 223–235 (2010)
Shin, J., Kim, H.: Nonlinear model predictive formation flight. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans 39(5), 1116–1125 (2009)
Saska, M., Mejia, J.S., Stipanovic, D.M., Schilling, K.: Control and navigation of formations of car-like robots on a receding horizon. In: Proc. of 3rd IEEE Multi-conference on Systems and Control (2009)
Faigl, J., Krajník, T., Chudoba, J., Přeučil, L., Saska, M.: Low-cost embedded system for relative localization in robotic swarms. In: IEEE International Conference on Robotics and Automation, ICRA (2013)
Kulich, M., Chudoba, J., Kosnar, K., Krajnik, T., Faigl, J., Preucil, L.: Syrotek - distance teaching of mobile robotics. IEEE Transactions on Education 56(1), 18–23 (2013)
Barfoot, T.D., Clark, C.M.: Motion planning for formations of mobile robots. Robotics and Autonomous Systems 46, 65–78 (2004)
Saska, M., Hess, M., Schilling, K.: Efficient airport snow shoveling by applying autonomous multi-vehicle formations. In: Proc. of IEEE International Conference on Robotics and Automation (May 2008)
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Saska, M., Spurný, V., Přeučil, L. (2013). Trajectory Planning and Stabilization for Formations Acting in Dynamic Environments. In: Correia, L., Reis, L.P., Cascalho, J. (eds) Progress in Artificial Intelligence. EPIA 2013. Lecture Notes in Computer Science(), vol 8154. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40669-0_28
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DOI: https://doi.org/10.1007/978-3-642-40669-0_28
Publisher Name: Springer, Berlin, Heidelberg
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