Title :
Motion-Driven Action-Based Planning
Author :
Ellenberger, Benjamin ; Mali, Amol D.
Author_Institution :
Nat. Insurance Services, Brookfield, WI, USA
Abstract :
Achievement of robotic goals generally needs both plan synthesis and plan execution through physical motions. Costs of actions in robotic tasks are generally motion-dependent. 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 action-based 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.
Keywords :
path planning; robots; action-based planner; motion planner; motion-driven action-based planning; motion-related cost; physical motions; plan execution; plan synthesis; robotic goal achievement; Artificial intelligence; Collision avoidance; Linear programming; Planning; Robot kinematics; Welding; Integrated Planning; Motion Planning; Optimal Planning; Task Planning;
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2013 IEEE 25th International Conference on
Conference_Location :
Herndon, VA
Print_ISBN :
978-1-4799-2971-9
DOI :
10.1109/ICTAI.2013.128