Autonomous indoor exploration with an event-based visual SLAM system

In this paper we present an autonomous mobile robot setting that automatically explores and maps unknown indoor environments, exclusively with information from an embedded event-based dynamic vision sensor (eDVS) and a ring of bump switches on the robot. The eDVS provides a sparse pre-processed visual signature of the currently visible patch of ceiling, which is used for real-time simultaneous localization and mapping (SLAM). Signals from the robot´s bump switches together with its current position estimate continuously improve the system´s reasoning about traversable areas. A heuristic path planning method motivated by the A* search algorithm generates routes for continuous autonomous exploration. We demonstrate robust real-time operation and evaluate the performance of our system in various indoor environments.