提出可保证飞行稳定性的模块化无人机自重构算法
Robust Self-Reconfiguration for Fault-Tolerant Control of Modular Aerial Robot Systems
- 基于可控性约束设计最优拆装序列，确保每步重构都可控制
- 在故障场景下实现更优轨迹跟踪，组装步骤减少30%以上
- 适合需要高可靠性的无人机集群系统研发人员使用
模块化空中机器人系统（MARS）由多个无人机单元组成，可集成成一个刚性飞行平台。由于具备冗余特性，MARS可在部分旋翼或单元失效时通过自重构调整结构，维持稳定飞行。然而，现有研究常忽略重构过程中中间构型的实际可控制性，限制了实用性。本文针对这一问题，考虑MARS的控制受限动力学模型，提出一种鲁棒高效的自重构算法，最大化每个中间阶段的可控性裕度。具体而言，我们设计算法计算最优、可控制的拆解与组装序列，实现稳健自重构。最后，在多个复杂故障容错重构场景中验证方法，结果表明其在可控性与轨迹跟踪性能上均有显著提升，同时减少30%以上的组装步骤。相关视频与源码见https://github.com/RuiHuangNUS/MARS-Reconfig/
原文摘要 · Abstract (English)
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/
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