Rousseas Panagiotis, Karras George C, Bechlioulis Charalampos P, Kyriakopoulos Kostas J
Control Systems Laboratory, National Technical University of Athens, 15772 Athens, Greece.
Department of Informatics and Telecommunications, University of Thessaly, 35100 Lamia, Greece.
Sensors (Basel). 2022 Jul 11;22(14):5194. doi: 10.3390/s22145194.
In this work, we develop a reactive algorithm for autonomous exploration of indoor, unknown environments for multiple autonomous multi-rotor robots. The novelty of our approach rests on a two-level control architecture comprised of an Artificial-Harmonic Potential Field (AHPF) for navigation and a low-level tracking controller. Owing to the AHPF properties, the field is provably safe while guaranteeing workspace exploration. At the same time, the low-level controller ensures safe tracking of the field through velocity commands to the drone's attitude controller, which handles the challenging non-linear dynamics. This architecture leads to a robust framework for autonomous exploration, which is extended to a multi-agent approach for collaborative navigation. The integration of approximate techniques for AHPF acquisition further improves the computational complexity of the proposed solution. The control scheme and the technical results are validated through high-fidelity simulations, where all aspects, from sensing and dynamics to control, are incorporated, demonstrating the capacity of our method in successfully tackling the multi-agent exploration task.
在这项工作中，我们为多个自主多旋翼机器人开发了一种用于自主探索室内未知环境的反应式算法。我们方法的新颖之处在于一种两级控制架构，该架构由用于导航的人工谐波势场（AHPF）和一个低级跟踪控制器组成。由于AHPF的特性，该场在保证工作空间探索的同时被证明是安全的。同时，低级控制器通过向无人机姿态控制器发送速度命令来确保对该场的安全跟踪，姿态控制器处理具有挑战性的非线性动力学。这种架构导致了一个用于自主探索的强大框架，该框架被扩展为一种用于协作导航的多智能体方法。用于获取AHPF的近似技术的集成进一步提高了所提出解决方案的计算复杂度。通过高保真模拟对控制方案和技术结果进行了验证，其中纳入了从传感、动力学到控制的所有方面，证明了我们的方法成功解决多智能体探索任务的能力。
