The design of robotic hands for dexterous grasping and manipulation in unstructured environments often leads to topologically complex anthropomorphic (biomimetic) solutions. These solutions, however elegant and intuitive, typically entail complex actuation frameworks, including dozens of motors and sensors, which make them expensive and difficult to implement effectively. In addition to cost of implementation issues, it is unclear whether biomimetic/biomorphic robotic hands are best suited to modern day actuation, sensing, and computing (vision, control).
We will investigate the design and control foundations of robotic hands using the following method: (1) Define the task/operational space of human manipulation in terms of experimentally acquired kinematic and kinetic properties, (2) develop reduced-dimension grasp control models which reveal grasp basis functions (eigengrasps), (3) use basis functions and characterized grasp mechanics to design underactuated compliant robotic hands in-silica (simulation, optimization), and (4) validate synthesized hand designs experimentally on industrial robotic manipulation platforms.
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