Formation Maintenance and Collision Avoidance in a Swarm of Drones

Abstract

Distributed formation control and obstacle avoidance are two important challenges in autonomous navigation of a swarm of drones and can negatively affect each other due to possible competition that arises between them. In such a platform, a multi-priority control strategy is required to be implemented in every node in order to dynamically optimise the tradeoffs between collision avoidance and formation control w.r.t. given system constraints, e.g. on energy and response time, by reordering priorities in run-time and selecting the suitable formation and collision avoidance approach based on the state of the swarm, i.e., the kinematic parameters and geographical distribution of the nodes as well as the location of the observed obstacles. In this paper, we propose a method for formation/collision co-awareness with the goal of energy consumption and response time minimisation. The algorithm consists of two partial nested feedback-based control loops and based on three observations: 1) for formation maintenance the relative location of the neighbour nodes; 2) observation of an obstacle by a local sensor, represented by a boolean value, used for both formation control and collision avoidance; and 3) in critical situations for avoiding collisions, the distance of an obstacle to the node. The obtained comprehensive experimental results show that the proposed approach appropriately keeps the formation during the swarm's travel in the presence of different obstacles.