Goal-Directed Scientific Exploration Using Multiple Rovers
Tara A. Estlin, Rebecca Castañ Ashley Davies, Darren Mutz, Gregg Rabideau, Steve Chien, Eric Mjolsness · 2001
Tt~is paper describes an integrated system for co-ordinating multiple rover behavior with the overall goal of collecting planetary surface data. The Multi-Rover Integrated Science Understanding System com-bines concepts from machine learning with planning and scheduling to perform autonomous scientific ex-ploration by cooperating rovers. The integrated system utilizes a novel machine-learning clustering component to analyze science data and direct new science activ-ities. A distributed planning and scheduling system is employed to generate rover plans for achieving sci-ence goals, to coordinate activities among rovers, and to replan when necessary. We describe each of these components and describe how they are integrated with a planetary environment simulation.