An AO* Algorithm for Planning with Continuous Resources

We consider the problem of optimal planning in stochastic domains with resource constraints, where resources are con- tinuous and the choice of action at each step may depend on the current resource level. Our principal contribution is the HAO* algorithm, a generalization of the AO* algorithm that performs search in a hybrid state space that is modeled using both discrete and continuous state variables. The search algo- rithm leverages knowledge of the starting state to focus com- putational effort on the relevant parts of the state space. We claim that this approach is especially effective when resource limitations contribute to reachability constraints. Experimen- tal results show its effectiveness in the domain that motivates our research - automated planning for planetary exploration rovers.