Data-driven optimization for underactuated robotic hands Ciocarlie Matei author Columbia University. Computer Science Allen Peter K. author Columbia University. Computer Science Columbia University. Computer Science originator text Articles 2010 English 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. Robotics 2010 IEEE International Conference on Robotics and Automation Piscataway, N.J. IEEE 2010 1292 1299 http://dx.doi.org/10.1109/ROBOT.2010.5509793 </titleInfo> </relatedItem> </relatedItem> <identifier type="hdl">http://hdl.handle.net/10022/AC:P:15086</identifier> <location> <physicalLocation authority="marcorg">NNC</physicalLocation> </location> <recordInfo> <recordContentSource authority="marcorg">NNC</recordContentSource> <recordCreationDate encoding="w3cdtf">2012-10-25 15:28:09 -0400</recordCreationDate> <recordChangeDate encoding="w3cdtf">2012-10-25 15:35:58 -0400</recordChangeDate> <recordIdentifier>9084</recordIdentifier> <languageOfCataloging> <languageTerm authority="iso639-2b">eng</languageTerm> </languageOfCataloging> </recordInfo> </mods>