The geophysical quantification of subsurfaces is a highly relevant topic in planetary exploration tasks. In particular, the Martian subsurface plays a major target since until now it remains mostly unexplored. More detailed quantification of the Martian subsurface will shed light on the question of life existence beyond Earth. Therefore, we aim at the development of a system that enables a subsurface exploration in an autonomous fashion. For its realization we use a swarm of multiple agents that acts as an intelligent network and explores the subsurface in a distributed and cooperative manner. Each agent acquires seismic data and cooperates with neighboring agents in order to obtain an image of the subsurface covered by the swarm. Furthermore, exploration strategies will be developed that direct the agents to new acquisition positions in order to improve the subsurface image. For the development phase we investigate the following techniques:
We examine these techniques with regard to a distributed implementation in a multi-agent network and develop corresponding algorithmic solutions. The developed algorithms will be tested in real experiments for seismic exploration tasks.