Distributed Swarm Collision Avoidance Based on Angular Calculations

TL;DR

This paper introduces a distributed, real-time collision avoidance algorithm for robot swarms in complex environments, utilizing angular calculations to improve speed and reliability over existing methods.

Contribution

It presents a novel distributed algorithm based on angular calculations that enhances collision avoidance efficiency and reliability in dense 2D and 3D environments.

Findings

At least 25% faster than ORCA

At least 7% faster than FMP

More reliable than both methods

Abstract

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.