Date of Award
Doctor of Philosophy (PhD)
Nancy S. Pollard
Christopher G. Atkeson
Jessica K. Hodgins
John M. Hollerbach
Robotic systems have yet to match humans in skill for movement planning
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 manipulation
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 performance
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
Chang, Lillian Y., "Pre-Grasp Interaction as a Manipulation Strategy for Movable Objects" (2010). Dissertations. Paper 42.