A Collaborative Localization and Guidance Method of Multiple UGVs for Logistics Delivery

This paper aims to investigate a collaborative localization and guidance method for a multi-heterogeneous unmanned ground vehicles (UGVs) to address the last-mile delivery problem in e-commerce. Firstly, this paper examines the use of Ultra-Wideband (UWB) technology to provide localization services for UGVs. By aggregating three UWB base stations into a group and deploying multiple clusters of UWB base stations using a dynamic particle swarm optimization algorithm, the interested area can be covered. Secondly, this paper transforms the cooperative guidance problem of multiple UGVs into an optimization problem, combining the Floyd algorithm and the Particle Swarm Optimization (PSO) algorithm as a heuristic algorithm for task allocation and path planning. This algorithm is further implemented as a distributed logistics controller (DLC) to enable all UGVs to collaborate within a group, aiming to achieve optimal task scheduling and minimize the longest completion time for all tasks. The proposed navigation and guidance methods are validated on a developed semi-physical simulation platform, and experimental results demonstrate that the UWB-based localization system can accurately guide the UGVs in complex paths, and the DLC effectively reduces the logistics delivery time while maintaining stability and reliability.