Sökning: "Robot Grasping"
Visar resultat 1 - 5 av 24 avhandlingar innehållade orden Robot Grasping.
1. From Human to Robot Grasping
Sammanfattning : Imagine that a robot fetched this thesis for you from a book shelf. How doyou think the robot would have been programmed? One possibility is thatexperienced engineers had written low level descriptions of all imaginabletasks, including grasping a small book from this particular shelf. LÄS MER
2. Dexterous Grasping : Representation and Optimization
Sammanfattning : Many robot object interactions require that an object is firmly held, and that the grasp remains stable during the whole manipulation process. Based on grasp wrench space, this thesis address the problems of measuring the grasp sensitivity against friction changes, planning contacts and hand configurations on mesh and point cloud representations of arbitrary objects, planning adaptable grasps and finger gaiting for keeping a grasp stable under various external disturbances, as well as learning of grasping manifolds for more accurate reachability and inverse kinematics computation for multifingered grasping. LÄS MER
3. Data-Efficient Representation Learning for Grasping and Manipulation
Sammanfattning : General-purpose robotics require adaptability to environmental variations and, therefore, need effective representations for programming them. A common way to acquire such representations is through machine learning. Machine learning has shown great potential in computer vision, natural language processing, reinforcement learning, and robotics. LÄS MER
4. Flexible Robot to Object Interactions Through Rigid and Deformable Cages
Sammanfattning : In this thesis we study the problem of robotic interaction with objects from a flexible perspective that complements the rigid force-closure approach. In a flexible interaction the object is not firmly bound to the robot (immobilized), which leads to many interesting scenarios. LÄS MER
5. Holistic Grasping: Affordances, Grasp Semantics, Task Constraints
Sammanfattning : Most of us perform grasping actions over a thousand times per day without giving it much consideration, be it from driving to drinking coffee. Learning robots the same ease when it comes to grasping has been a goal for the robotics research community for decades. LÄS MER