TY - GEN

T1 - Design of non-anthropomorphic robotic hands for anthropomorphic tasks

AU - Simo-Serra, Edgar

AU - Moreno-Noguer, Francesc

AU - Perez-Gracia, Alba

PY - 2011

Y1 - 2011

N2 - In this paper, we explore the idea of designing non-anthropomorphic multi-fingered robotic hands for tasks that replicate the motion of the human hand. Taking as input data a finite set of rigid-body positions for the five fingertips, we develop a method to perform dimensional synthesis for a kinematic chain with a tree structure, with five branches that share three common joints. We state the forward kinematics equations of relative displacements for each serial chain expressed as dual quaternions, and solve for up to five chains simultaneously to reach a number of positions along the hand trajectory. This is done using a hybrid global numerical solver that integrates a genetic algorithm and a Levenberg-Marquardt local optimizer. Although the number of candidate solutions in this problem is very high, the use of the genetic algorithm allows us to perform an exhaustive exploration of the solution space to obtain a set of solutions. We can then choose some of the solutions based on the specific task to perform. Note that these designs match the task exactly while generally having a finger design radically different from that of the human hand.

AB - In this paper, we explore the idea of designing non-anthropomorphic multi-fingered robotic hands for tasks that replicate the motion of the human hand. Taking as input data a finite set of rigid-body positions for the five fingertips, we develop a method to perform dimensional synthesis for a kinematic chain with a tree structure, with five branches that share three common joints. We state the forward kinematics equations of relative displacements for each serial chain expressed as dual quaternions, and solve for up to five chains simultaneously to reach a number of positions along the hand trajectory. This is done using a hybrid global numerical solver that integrates a genetic algorithm and a Levenberg-Marquardt local optimizer. Although the number of candidate solutions in this problem is very high, the use of the genetic algorithm allows us to perform an exhaustive exploration of the solution space to obtain a set of solutions. We can then choose some of the solutions based on the specific task to perform. Note that these designs match the task exactly while generally having a finger design radically different from that of the human hand.

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U2 - 10.1115/DETC2011-47818

DO - 10.1115/DETC2011-47818

M3 - Conference contribution

AN - SCOPUS:84863560874

SN - 9780791854839

T3 - Proceedings of the ASME Design Engineering Technical Conference

SP - 377

EP - 386

BT - ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2011

T2 - ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2011

Y2 - 28 August 2011 through 31 August 2011

ER -