Conditional planning enables planning for 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 algorithm that incrementally constructs a hybrid conditional plan using parallel instances of a nonmonotonic hybrid planner. We show an application of hybrid conditional planning for robotics with a service robotics scenario where a mobile manipulator sets up a kitchen table, and evaluate our parallel planner over various mobile manipulation scenarios from the perspectives of computational efficiency and plan quality.
Esra Erdem is an associate professor in computer science and engineering at Sabanci University. She received her Ph.D. in computer sciences at the University of Texas at Austin (2002), and carried out postdoctoral research at the University of Toronto and Vienna University of Technology from 2002 to 2006.Her research is in the area of artificial intelligence, in particular, the mathematical foundations of knowledge representation and reasoning, and their applications to cognitive robotics and computational biology.