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

arXiv: https://arxiv.org/abs/2104.07741 · HTML: https://mlsanity.com/paper/2104.07741/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Apr 2021.

## Built on by (most cited first, 2 of 2)

- [Deep Q-Learning-Based Gain Scheduling for Nonlinear Quadcopter Dynamics](https://mlsanity.com/paper/2603.03127/) (2026)
- [Online Reinforcement Learning for Safe Gain Scheduling in Nonlinear Quadrotor Control](https://mlsanity.com/paper/2604.16819/) (2026)

## Abstract (arXiv)

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.