Petráček Pavel, Walter Viktor, Báča Tomáš, Saska Martin
Department of Cybernetics, Czech Technical University in Prague, Karlovo namesti 13, 12135 Prague 2, Praha, 160 00, CZECH REPUBLIC.
Department of Cybernetics, Czech Technical University in Prague, Praha, CZECH REPUBLIC.
Bioinspir Biomim. 2020 Nov 2. doi: 10.1088/1748-3190/abc6b3.
This article presents a unique framework for deploying decentralized and infrastructure-independent swarms of homogeneous aerial vehicles in the real world without explicit communication. This is a requirement in swarm research, which anticipates that global knowledge and communication will not scale well with the number of robots. The system architecture proposed in this article employs the UVDAR technique to directly perceive the local neighborhood for direct mutual localization of swarm members. The technique allows for decentralization and high scalability of swarm systems, such as can be observed in fish schools, bird flocks, or cattle herds. The bio-inspired swarming model that has been developed is suited for real-world deployment of large particle groups in outdoor and indoor environments with obstacles. The collective behavior of the model emerges from a set of local rules based on direct observation of the neighborhood using onboard sensors only. The model is scalable, requires only local perception of agents and the environment, and requires no communication among the agents. Apart from simulated scenarios, the performance and usability of the entire framework is analyzed in several real-world experiments with a fully-decentralized swarm of UAV deployed in outdoor conditions. To the best of our knowledge, these experiments are the first deployment of decentralized bio-inspired compact swarms of UAV without the use of a communication network or shared absolute localization. The entire system is available as open-source at https://github.com/ctu-mrs.
本文提出了一个独特的框架，用于在现实世界中部署分散且独立于基础设施的同类飞行器群，且无需明确通信。这是群体研究中的一项要求，因为预计全球知识和通信随着机器人数量的增加将无法很好地扩展。本文提出的系统架构采用超视距有源雷达（UVDAR）技术直接感知局部邻域，以实现群体成员的直接相互定位。该技术可实现群体系统的分散化和高扩展性，比如在鱼群、鸟群或牛群中就能观察到这种特性。所开发的受生物启发的群体模型适用于在有障碍物的室外和室内环境中对大型粒子群进行实际部署。该模型的集体行为仅源于一组基于仅使用机载传感器对邻域进行直接观察的局部规则。该模型具有可扩展性，只需要智能体对自身和环境进行局部感知，且智能体之间无需通信。除了模拟场景外，还通过在户外条件下部署完全分散的无人机群进行了几次实际实验，分析了整个框架的性能和可用性。据我们所知，这些实验是首次在不使用通信网络或共享绝对定位的情况下，对受生物启发的分散紧凑型无人机群进行部署。整个系统可在https://github.com/ctu-mrs上作为开源代码获取。
