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UWB Role Allocation with Distributed Ledger Technologies for Scalable Relative Localization in Multi-Robot Systems

2022/08/29 by Paola Torrico Morón, Morón, Paola Torrico, Salma Salimi +5
Computer Science · Engineering · #FOS: Computer and information sciences #Mobile Ad Hoc Networks #Robotics (cs.RO) #Security in Wireless Sensor Networks #Wireless Body Area Networks

paper · pdf · doi:10.48550/arxiv.2208.13546

openalex publication_date 2022/08/29 · openalex created_date 2022/08/31 · openalex updated_date 2026/07/28

Abstract

Systems for relative localization in multi-robot systems based on ultra-wideband (UWB) ranging have recently emerged as robust solutions for GNSS-denied environments. Scalability remains one of the key challenges, particularly in ad-hoc deployments. Recent solutions include dynamic allocation of active and passive localization modes for different robots or nodes in the system. With larger-scale systems becoming more distributed, key research questions arise in the areas of security and trustability of such localization systems. This paper studies the potential integration of collaborative-decision making processes with distributed ledger technologies. Specifically, we investigate the design and implementation of a methodology for running an UWB role allocation algorithm within smart contracts in a blockchain. In previous works, we have separately studied the integration of ROS2 with the Hyperledger Fabric blockchain, and introduced a new algorithm for scalable UWB-based localization. In this paper, we extend these works by (i) running experiments with larger number of mobile robots switching between different spatial configurations and (ii) integrating the dynamic UWB role allocation algorithm into Fabric smart contracts for distributed decision-making in a system of multiple mobile robots. This enables us to deliver the same functionality within a secure and trustable process, with enhanced identity and data access management. Our results show the effectiveness of the UWB role allocation for continuously varying spatial formations of six autonomous mobile robots, while demonstrating a low impact on latency and computational resources of adding the blockchain layer that does not affect the localization process.

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