Distributed Swarm Collision Avoidance Based on Angular Calculations
This addresses efficient and safe navigation for autonomous robot swarms, representing an incremental improvement over existing methods.
The paper tackles collision avoidance for robot swarms in dense 2D/3D environments by proposing a distributed real-time algorithm using angular calculations, achieving at least 25% faster performance than ORCA and 7% faster than FMP with improved reliability.
Collision avoidance is one of the most important topics in the robotics field. The goal is to move the robots from initial locations to target locations such that they follow shortest non-colliding paths in the shortest time and with the least amount of energy. In this paper, a distributed and real-time algorithm for dense and complex 2D and 3D environments is proposed. 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 FMP and ORCA, two important algorithms in this field. The results show that the proposed approach is at least 25% faster than ORCA and at least 7% faster than FMP and also more reliable than both methods. The proposed method is shown to enable fully autonomous navigation of a swarm of crazyflies.