Cellular Formation Maintenance and Collision Avoidance Using Centroid-Based Point Set Registration in a Swarm of Drones

TL;DR

This paper presents a novel approach for collision avoidance and formation reformation in drone swarms, utilizing cellular automata and point set registration techniques to minimize energy and time consumption.

Contribution

It introduces a new method combining cellular automata and temperature function reduction for efficient collision avoidance and formation reformation in drone swarms.

Findings

Effective collision avoidance with minimal formation disturbance

Reduced energy consumption during reformation

Improved swarm reformation speed

Abstract

This work focuses on low-energy collision avoidance and formation maintenance in autonomous swarms of drones. Here, the two main problems are: 1) how to avoid collisions by temporarily breaking the formation, i.e., collision avoidance reformation, and 2) how do such reformation while minimizing the deviation resulting in minimization of the overall time and energy consumption of the drones. To address the first question, we use cellular automata based technique to find an efficient formation that avoids the obstacle while minimizing the time and energy. Concerning the second question, a near-optimal reformation of the swarm after successful collision avoidance is achieved by applying a temperature function reduction technique, originally used in the point set registration process. The goal of the reformation process is to remove the disturbance while minimizing the overall time it takes for the swarm to reach the destination and consequently reducing the energy consumption required by this operation. To measure the degree of formation disturbance due to collision avoidance, deviation of the centroid of the swarm formation is used, inspired by the concept of the center of mass in classical mechanics. Experimental results show the efficiency of the proposed technique, in terms of performance and energy.