Zero-Trust-Based Privacy-Preserving Distributed Localization for Mobile Robot Networks

• 成果类型: Article
• 署名作者: Shi, Lei; Huang, Darong; Zong, Guangdeng; Zhou, Yi; Cheng, Yuhua
• 署名单位: Henan University; Anhui University; Tiangong University; University of Electronic Science & Technology of China
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2025.3597945
• 发表日期: 2026
• 关键词: COOPERATIVE LOCALIZATION; sensor networks

摘要

Localization is the foundation for achieving autonomous navigation of robots, and protecting the privacy of robots during the localization process is crucial. This article develops a zero-trust-based privacy-preserving distributed iteration localization (ZTPP-DILOC) algorithm for a robot network that moves freely within bounded areas. In this algorithm, based on the principle of never trust, always verify in the zero-trust security framework, real-time trust evaluation mechanisms are established for both sent and received information. On the one hand, each robot evaluates its trust degree for nearby robots, and integrates the historical information to generate false location estimation values for sending, thereby protecting the security of information transmission. On the other hand, each robot evaluates its trust degree for the received information, and generates a time-varying iterative equation, thereby protecting the security of location estimation update rules. A comprehensive analysis is conducted on the convergence, complexity, and privacy-preserving performance of the ZTPP-DILOC algorithm, relying on edge combination and substochastic matrix techniques. The ZTPP-DILOC algorithm is shown to be capable of accurate localization without disclosing the real locations of robots. At last, the effectiveness of the algorithm is verified through computer simulations and experiments.