Safe Affine Transformation-Based Guidance of a Large-Scale Multi-Quadcopter System (MQS)

TL;DR

This paper presents a decentralized affine transformation guidance method for large-scale multi-quadcopter systems, ensuring safety and optimal coordination in obstacle-rich environments through eigenvalue constraints and A-star planning.

Contribution

It introduces a novel affine transformation-based guidance approach with safety guarantees, decentralized control, and efficient communication topology for large-scale MQS coordination.

Findings

Eigen-decomposition ensures safety via eigenvalue constraints.

A-star search optimally plans safe trajectories.

Proximity-based communication reduces computational costs.

Abstract

This paper studies the problem of affine transformation-based guidance of a multi-quadcopter system (MQS) in an obstacle-laden environment. Such MQSs can perform a variety of cooperative tasks including information collection, inspection mapping, disinfection, and firefighting. The MQS affine transformation is an approach to a decentralized leader-follower coordination guided by n +1 leaders, where leaders are located at vertices of an n-D simplex, called leading simplex, at any time t. The remaining agents are followers acquiring the desired affine transformation via local communication. Followers are contained in a rigid-size ball at any time t but they can be distributed either inside or outside the leading simplex. By eigen-decomposition of the affine transformation coordination, safety in a large-scale MQS coordination can be ensured by constraining eigenvalues of the affine transformation. Given the initial and final configurations of the MQS, A-star search is applied to optimally plan safe coordination of a large-scale MQS minimizing the travel distance between the the initial and final configuration. The paper also proposes a proximity-based communication topology for followers to assign communication weights with their in-neighbors and acquire the desired coordination with minimal computation cost.