School of Information, Renmin University of China, Beijing 100872, China.
Metaverse Research Center, Renmin University of China, Beijing 100872, China.
Sensors (Basel). 2023 Feb 21;23(5):2399. doi: 10.3390/s23052399.
For a network of robots working in a specific environment, relative localization among robots is the basis for accomplishing various upper-level tasks. To avoid the latency and fragility of long-range or multi-hop communication, distributed relative localization algorithms, in which robots take local measurements and calculate localizations and poses relative to their neighbors distributively, are highly desired. Distributed relative localization has the advantages of a low communication burden and better system robustness but encounters challenges in the distributed algorithm design, communication protocol design, local network organization, etc. This paper presents a detailed survey of the key methodologies designed for distributed relative localization for robot networks. We classify the distributed localization algorithms regarding to the types of measurements, i.e., distance-based, bearing-based, and multiple-measurement-fusion-based. The detailed design methodologies, advantages, drawbacks, and application scenarios of different distributed localization algorithms are introduced and summarized. Then, the research works that support distributed localization, including local network organization, communication efficiency, and the robustness of distributed localization algorithms, are surveyed. Finally, popular simulation platforms are summarized and compared in order to facilitate future research and experiments on distributed relative localization algorithms.
对于在特定环境中工作的机器人网络，机器人之间的相对定位是完成各种上层任务的基础。为了避免远程或多跳通信的延迟和脆弱性，分布式相对定位算法应运而生，其中机器人在本地进行测量，并分布式地计算相对于邻居的本地定位和姿态。分布式相对定位具有通信负担低和系统鲁棒性好的优点，但在分布式算法设计、通信协议设计、本地网络组织等方面存在挑战。本文详细调查了用于机器人网络的分布式相对定位的关键方法。我们根据测量类型对分布式定位算法进行分类，即基于距离、基于方位和基于多测量融合。介绍并总结了不同分布式定位算法的详细设计方法、优点、缺点和应用场景。然后，调查了支持分布式定位的研究工作，包括本地网络组织、通信效率和分布式定位算法的鲁棒性。最后，总结并比较了流行的仿真平台，以便于未来对分布式相对定位算法的研究和实验。
