Robust Self-Reconfiguration for Fault-Tolerant Control of Modular Aerial Robot Systems

Abstract

Modular Aerial Robotic Systems (MARS) consist of multiple drone units assembled into a single, integrated rigid flying platform. With inherent redundancy, MARS can self-reconfigure into different configurations to mitigate rotor or unit failures and maintain stable flight. However, existing works on MARS self-reconfiguration often overlook the practical controllability of intermediate structures formed during the reassembly process, which limits their applicability. In this paper, we address this gap by considering the control-constrained dynamic model of MARS and proposing a robust and efficient self-reconstruction algorithm that maximizes the controllability margin at each intermediate stage. Specifically, we develop algorithms to compute optimal, controllable disassembly and assembly sequences, enabling robust self-reconfiguration. Finally, we validate our method in several challenging fault-tolerant self-reconfiguration scenarios, demonstrating significant improvements in both controllability and trajectory tracking while reducing the number of assembly steps. The videos and source code of this work are available at https://github.com/RuiHuangNUS/MARS-Reconfig/