Manipulation Planning with Caging Grasps

We present a novel motion planning algorithm for performing constrained tasks such as opening doors and drawers by robots such as humanoid robots or mobile manipulators. Previous work on constrained manipulation transfers rigid constraints imposed by the target object motion directly into the robot configuration space. This often unnecessarily restricts the allowable robot motion, which can prevent the robot from performing even simple tasks, particularly if the robot has limited reachability or low number of joints. Our method computes caging grasps specific to the object and uses efficient search algorithms to produce motion plans that satisfy the task constraints. The major advantages of our technique significantly increase the range of possible motions of the robot by not having to enforce rigid constraints between the end-effector and the target object. We illustrate our approach with experimental results and examples running on two robot platforms.