Abstract
Collision avoidance is one of the most important topics in the robotics field. In this problem, the goal is to move the robots from initial locations to target locations such that they follow the shortest non-colliding paths in the shortest time and with the least amount of energy. Robot navigation among pedestrians is an example application of this problem which is the focus of this paper. This paper presents a distributed and real-time algorithm for solving collision avoidance problems in dense and complex 2D and 3D environments. This algorithm uses angular calculations to select the optimal direction for the movement of each robot and it has been shown that these separate calculations lead to a form of cooperative behavior among agents. We evaluated the proposed approach on various simulation and experimental scenarios and compared the results with ORCA one of the most important algorithms in this field. The results show that the proposed approach is at least 25% faster than ORCA while is also more reliable. The proposed method is shown to enable fully autonomous navigation of a swarm of Crazyflies.
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Acknowledgements
The authors would like to thank professor Hugh H.T. Liu from the University of Toronto for his helpful comments on this work.
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Qazavi, S., Semnani, S.H. Distributed swarm collision avoidance based on angular calculations. Auton Robot 47, 425–434 (2023). https://doi.org/10.1007/s10514-022-10081-6
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DOI: https://doi.org/10.1007/s10514-022-10081-6