Information-Seeking in Localization and Mission Planning of Multi-Agent Systems

Kyriakos Lite, Bernhard Rinner

Abstract: Real-time and accurate position estimation is critical for various multi-robot applications and serves as a prerequisite for location-based multi-sensor data analysis. However, it is often impeded by energy, sensing, and processing limitations. In this work, we study the problem of information-seeking in localization and navigation in multi-agent systems, which aims to navigate mobile agents while reducing position errors. We formalize information-seeking as reducing spatial uncertainty and introduce an efficient motion controller based on artificial potential fields superimposing attractive, repulsive, and information-seeking forces. We evaluate the effect of information-seeking on localization and mission planning in a simulation study with non-collaborative and collaborative localization approaches.