Experimental Evaluation of Hybrid Conditional Planning for Service Robotics

Conditional planning enables planning for the sensing actions and their possible outcomes in addition to actuation actions, and allows for addressing uncertainties due to partial observability at the time of offline planning. Therefore, the plans (called conditional plans) computed by conditional planners can be viewed as trees of (deterministic) actuation actions and (nondeterministic) sensing actions. Hybrid conditional planning extends conditional planning further by integrating low-level feasibility checks into executability conditions of actuation actions in conditional plans. We introduce a novel hybrid conditional planning method, which extends hybrid sequential planning with nondeterministic sensing actions and utilizes this extension to compute branches of a conditional plan in parallel. We evaluate this method in a service robotics domain, by means of a set of experiments over dynamic simulations, from the perspectives of computational efficiency and plan quality.