C-TM: Topo-metric Mapping and Localization based on Place Categorization and Place Recognition for a Delivery Robot on Footpath

Abstract

In this work, C-TM is presented: a method to build a topo-metric map for delivery robot navigation in largescale city environments. This system automatically generates a compact map by only saving expensive LIDAR information at key locations. These locations form the nodes of a topological map. Nodes are identified using a Place-Categorization (PC) neural network which output the place category from RGB cameras. Inside nodes, we generate and save high quality LIDAR submaps. Global localization within the map is done with a Visual-Place-Recognition (VPR) neural network. The topo-metric map can be used for navigation on footpath. We deploy C-TM on a four-wheeled autonomous delivery robot and test the effectiveness in two environments, both day and night.