Online Collaborative Radio-enhanced Visual-inertial SLAM

Abstract: Simultaneous localization and mapping (SLAM) allows robots and other devices to localize and navigate in environments by using a map which itself generates. SLAM for single agent applications has matured and is showing promising results, thus the interest for collaborative SLAM has increased.This thesis proposes a framework for online collaborative radio-enhanced visual-inertial (VI) SLAM where multiple agents can collaborate by having their individually built maps merged and shared amongst each other. The framework is centralized with the aim to allow multiple agents to be managed by a single machine, also rendering it feasible to use the framework with agents that have limited computational resources, e.g. nano drones. Furthermore, radio technology is implemented in the framework which augments the SLAM solution by fusing ultra-wideband (UWB) anchor information into the built maps. This enables agents to query relevant parts of potentially large maps based on their contemporary radio activity.Four individual experiments are conducted to thoroughly evaluate the proposed solution. The results show that the collaborative SLAM system successfully allow agents to localize on parts of a map that other agents have built, running simultaneously. Moreover, the results also show that fusing UWB information into a visual-inertial map allow agents to perform partial-map queries, restricting the search area for visual matches between camera images and the map, reducing the risk of false re-localizations.