Motion-Driven Action-Based Planning

Achievement of robotic goals generally needs both plan synthesis and plan execution through physical motions. Costs of actions in robotic tasks are generally motiondependent. Generally there are many action-based plans for achieving a goal and usually there are many motion plans for executing each action-based plan. Many efficient actionbased planners and motion planners have been developed in the last twenty years. One can exploit these computational advances to find low-cost motion plans from the space of motion plans for executing a large number of action-based plans. In this paper we report on generation of action-based plans with low motion-related cost for their execution. We report on empirical evaluation which shows that the motion-related costs for executing action-based plans found with our approach are lower than those for action-based plans found with no motion cost information available to the action-based planner.