Heuristic search value iteration for POMDPs
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Probabilistic planning for robotic exploration
Probabilistic planning for robotic exploration
Point-based value iteration: an anytime algorithm for POMDPs
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Incremental pruning: a simple, fast, exact method for partially observable Markov decision processes
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
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Future Mars rovers will have the ability to autonomously navigate for distances of kilometers. In one sol a traverse may take a rover into unexplored areas beyond its local horizon. The rover can explore these areas more effectively if it is able to detect and react to science opportunities on its own, what we call science autonomy. We are studying science autonomy in two ways: first, by implementing a simple science autonomy system, In a rover in the field, and second, by developing probabilistic planning technology that can enable more principled autonomous decision-making in future systems.