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Data-driven optimization for underactuated robotic hands

Matei Ciocarlie; Peter K. Allen

Title:
Data-driven optimization for underactuated robotic hands
Author(s):
Ciocarlie, Matei
Allen, Peter K.
Date:
Type:
Articles
Department:
Computer Science
Permanent URL:
Book/Journal Title:
2010 IEEE International Conference on Robotics and Automation
Publisher:
IEEE
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
Publisher DOI:
http://dx.doi.org/10.1109/ROBOT.2010.5509793
Item views:
108
Metadata:
text | xml

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