Multi-mobile Robot Autonomous Navigation System for Intelligent Logistics

In order to improve the rapidity and robustness of the mobile robot's autonomous navigation system, combining with the new demand of the logistics industry by the explosive growth of the e-commerce industry, this paper designs a fast multi-mobile robot autonomous navigation system for intelligent logistics. Firstly, the RBPF-SLAM (simultaneous localization and mapping based on Rao-Blackwellized particle filter) algorithm is used to construct a 2D grid map of the work environment. Secondly, the ARA* (Anytime Repairing A*) global path planning and DWA (Dynamic Window Approach) local path planning are combined to quickly search for the optimal path to the target location and avoid static and dynamic obstacles; On this basis, the speed switching controller is designed according to the slope value, which improves the stability of the mobile robot uphill. Finally, three groups of navigation experiments are conducted on the several real mobile robots TurtleBot2 in complex indoor and outdoor environments, including indoor unmanned sorting, indoor self-delivery and outdoor self-delivery. The experimental results show that the designed mobile robot autonomous navigation system can quickly avoid the dynamic obstacles and reach the target position autonomously, which can further improve the intelligent level and delivery efficiency of the logistics delivery system.