Pre-grasp interaction as a manipulation strategy for movable objects

Abstract

Robotic systems have yet to match humans in skill for movement plan- ning and tool manipulation. For example, humans can robustly grasp and manipulate objects even under task variation. However, successful grasping methods for robotic manipulators are often limited to structured environmental conditions. Our dual goals are to understand manipula- tion actions in humans and to add such skills to a robot manipulator’s repertoire. In particular, we examine strategies for object acquisition, which is a common first component in manipulation actions. Many approaches to automating robot motion for object acquisition have focused on reach-to-grasp tasks, where the arm motion and hand configuration are planned for grasping an object. With these solutions, the object placement often remains fixed in the environment until the object is carefully grasped from its presented configuration. In contrast, humans often take advantage of an object’s movability to reorient and regrasp an object during the acquisition process. This thesis investigates how such pre-grasp interaction can improve grasping through preparatory manipulation of the object’s configuration. Specifically we studied the strategy of pre-grasp object rotation for grasp acquisition prior to a transport task. First, we examined human perfor- mance of the pre-grasp rotation strategy. A larger amount of pre-grasp object rotation correlated to a greater lifting capability, or maximum payload, of the grasping posture used at the time of object acquisition. In addition, when the task was more difficult due to increased object mass or increased upright orientation constraints, there was decreased variability in the object orientation selected for grasping. Second, we developed and evaluated a method for planning pre-grasp rotation for a robot manipulator. Our results show that the pre-grasp rotation strategy can improve a robot’s manipulation capabilities by both extending the effective workspace for a transport task and improving the quality of the transport action.