Enabling a Mobile Robot for Autonomous RFID-Based Inventory by Multilayer Mapping and ACO-Enhanced Path Planning

摘要

Paper presents a novel application for an autonomous robot to perform RFID-based inventory in a retail environment. For this application, one challenge is to represent a complicated environment by a good quality map. LIDAR (light detection and ranging) sensors only generate a 2D plane map that loses a large amount of structural information. In contrast, stereo or RGB-D cameras provide abundant environmental information but in a limited field of view (FOV), which limits the robot’s ability to gain reliable poses. Another challenge is effectively counting inventory within a massive retail environment; the robot needs to navigate in an optimal route that covers the entire target area.