Data-driven optimization for underactuated robotic hands

Articles:

Title:: Data-driven optimization for underactuated robotic hands
Author(s):: Ciocarlie, Matei
Allen, Peter K.
Date:: 2010
Type:: Articles
Department:: Computer Science
Permanent URL:: http://hdl.handle.net/10022/AC:P:15086
Book/Journal Title:: 2010 IEEE International Conference on Robotics and Automation
Publisher:: IEEE
Publisher Location:: Piscataway, N.J.
Abstract:: Passively adaptive and underactuated robotic hands have shown the potential to achieve reliable grasping in unstructured environments without expensive mechanisms or sensors. Instead of complex run-time algorithms, such hands use design-time analysis to improve performance for a wide range of tasks. Along these directions, we present an optimization framework for underactuated compliant hands. Our approach uses a pre-defined set of grasps in a quasistatic equilibrium formulation to compute the actuation mechanism design parameters that provide optimal performance. We apply our method to a class of tendon-actuated hands; for the simplified design of a two-fingered gripper, we show how a global optimum for the design optimization problem can be computed. We have implemented the results of this analysis in the construction of a gripper prototype, capable of a wide range of grasping tasks over a variety of objects.
Subject(s):: Robotics
DOI:: http://dx.doi.org/10.1109/ROBOT.2010.5509793