Dynamic Formation Reshaping Based on Point Set Registration in a Swarm of Drones

TL;DR

This paper presents a method for dynamically reshaping drone swarms into desired formations efficiently, using point set registration techniques to minimize deviation and time during reformation, especially in obstacle navigation.

Contribution

It introduces routines for optimal formation reshaping and applies point set registration with temperature function reduction for efficient multi-agent reformation.

Findings

Effective reshaping during obstacle navigation

Minimized deviation and reformation time

Successful dynamic shape adaptation

Abstract

This work focuses on the formation reshaping in an optimized manner in autonomous swarm of drones. Here, the two main problems are: 1) how to break and reshape the initial formation in an optimal manner, and 2) how to do such reformation while minimizing the overall deviation of the drones and the overall time, i.e., without slowing down. To address the first problem, we introduce a set of routines for the drones/agents to follow while reshaping to a secondary formation shape. And the second problem is resolved by utilizing the temperature function reduction technique, originally used in the point set registration process. The goal is to be able to dynamically reform the shape of multi-agent based swarm in near-optimal manner while going through narrow openings between, for instance obstacles, and then bringing the agents back to their original shape after passing through the narrow passage using point set registration technique.