Future robotic exploration using honeybee search strategy: Example search for caves on Mars

Autonomous control has an increasing role in Earth and Space based applications. High level autonomy can greatly improve planetary exploration and is, in many cases, essential. It has been suggested during the Mars cave exploration programme, that an effective way to explore a larger surface area would be the use of many, small and fully autonomous robots. However, there are many challenges to overcome if such a swarm exploration programme is to be implemented. This paper summarises these challenges and focuses on one of the most crucial one: strategy. Many effective group exploration behaviours can be observed in nature, most of which are optimised to work with agents that have limited capabilities as individuals. For this paper a computer program has been written to simulate the way bees search for new hives and investigate whenever it is an optimal method to search for cave entrances on Mars. It has been found that this method, using simple autonomous robots which can be constructed using available technologies, could greatly improve the speed and range of a planetary exploration mission. The simulation results show that 50 swarm robots can cover an area of over 300 meters square completely in 5 sols while they are searching for cave entrances and returning results to the Lander which is a major performance improvement on any previous mission. Furthermore areas of interests found by the explorers are sorted in order of importance automatically and without the need of computational analysis, hence larger quantities of data were collected from the more important areas. Therefore the system – just like a hive of bees – can make a complex decision easily and quickly to find the place which matches the required criteria best. Using a high performance search strategy such as the one described in this paper is crucial if we plan to search for important resources or even life on Mars and other bodies in the solar system.