Task planning for dextrous manipulation using blind grasping tele-assistance

An approach to operator interaction for a dextrous manipulator is described, using a tele-assistance method termed blind grasping. Given approximate initial coordinates for the object location, the blind grasping approach sequences a series of dextrous finger contact movements to establish the object geometry and candidate stable grasp locations. The approach is implemented within the framework of the preference planning tele-assistant task planning architecture. Geometric and semantic models of the world are used as triggers into pre-stored lists of action sequences. Actions are triggered when their pre-conditions fail, representing a state in the world that the action can correct. Failure of the action to change the world state hierarchically triggers sub-actions, until atomic actions instruct lower levels of control. For the first prototype AMADEVS dextrous underwater gripper, it is demonstrated that variously shaped objects centred between the open gripper fingers can generally be grasped using simple closure. However, off-centre displacements as small as 1 cm require five touch samples to acquire the geometry with sufficient accuracy to choose stable grasp contact points.