Automated site preparation on the Moon using a group of autonomous rovers is a topic of great interest for the establishment of a lunar base. A potentially very useful system in which multiple, autonomous rovers clear soil to create a landing pad while simultaneously forming berms with the soil cleared will be described. An Artificial Neural Tissue (ANT) architecture was used as the control algorithm to accomplish these tasks. This scalable architecture encourages task decomposition of the main mission tasks and requires minimal human supervision. To solve these tasks, a single fitness function to measure the performance of the controller and a set of allowable basis behaviors was defined. Next, an evolutionary (Darwinian) selection process was used to generate controllers in simulation. The fittest controller was subsequently implemented on LEGO robots for additional validation and testing. The ANT controller was ultimately integrated with a team of three large-scale rovers.

Automated site preparation on the Moon using a group of autonomous rovers is a topic of great interest for the establishment of a lunar base. A potentially very useful system in which multiple, autonomous rovers clear soil to create a landing pad while simultaneously forming berms with the soil cleared will be described. An Artificial Neural Tissue (ANT) architecture was used as the control algorithm to accomplish these tasks. This scalable architecture encourages task decomposition of the main mission tasks and requires minimal human supervision. To solve these tasks, a single fitness function to measure the performance of the controller and a set of allowable basis behaviors was defined. Next, an evolutionary (Darwinian) selection process was used to generate controllers in simulation. The fittest controller was subsequently implemented on LEGO robots for additional validation and testing. The ANT controller was ultimately integrated with a team of three large-scale rovers.