Spatio-Temporal Exploration Strategies for Long-Term Autonomy of Mobile Robots Jo˜ ao Machado Santos a , Tom´ aˇ s Krajn´ ık a , Tom Duckett a a Lincoln Centre for Autonomous Systems, University of Lincoln, Brayford Pool, Lincoln, Lincolnshire, LN6 7TS, United Kingdom Abstract We present a study of spatio-temporal environment representations and ex- ploration strategies for long-term deployment of mobile robots in real-world, dynamic environments. We propose a new concept for life-long mobile robot spatio-temporal exploration that aims at building, updating and maintain- ing the environment model during the long-term deployment. The addi- tion of the temporal dimension to the explored space makes the exploration task a never-ending data-gathering process, which we address by applica- tion of information-theoretic exploration techniques to world representations that model the uncertainty of environment states as probabilistic functions of time. We evaluate the performance of different exploration strategies and temporal models on real-world data gathered over the course of sev- eral months. The combination of dynamic environment representations with information-gain exploration principles allows to create and maintain up-to- date models of continuously changing environments, enabling efficient and self-improving long-term operation of mobile robots. Keywords: mobile robotics, spatio-temporal exploration, long-term autonomy 1. Introduction As robots gradually leave the well-structured worlds of factory assembly lines and enter natural, human-populated environments, new challenges ap- Email addresses: jsantos@lincoln.ac.uk (Jo˜ ao Machado Santos), tkrajnik@lincoln.ac.uk (Tom´aˇ s Krajn´ ık), tduckett@lincoln.ac.uk (Tom Duckett) Preprint submitted to Robotics and Autonomous Systems September 12, 2016