Throughout this book, we have described how neuroscientific findings on synergistic organization of human hand can be used to devise guidelines for the design and control of robotic and prosthetic hands as well as for sensing devices (see Chaps. 8, 10, 11 and 15). However, the development of novel robotic devices open issues on how to generalize the outcomes to different architectures. In this chapter, we describe a mapping strategy to transfer human hand synergies onto robotic hands with dissimilar kinematics. The algorithm is based on the definition of two virtual objects that are used to abstract from the specific structures of the hands. The proposed mapping strategy allows to overcame the problems in defining synergies for robotic hands computing PCA analysis over a grasp dataset obtained empirically closing the robot hand upon different objects. The developed mapping framework has been implemented using the SynGrasp Matlab toolbox. This tool includes functions for the definition of hand kinematic structure and of the contact points with a grasped object, the coupling between joints induced by a synergistic control, compliance at the contact, joint and actuator levels. Its analysis functions can be used to investigate the main grasp properties: controllable forces and object displacements, manipulability analysis, grasp quality measures. Furthermore, functions for the graphical representation of the hand, the object and the main analysis results are provided.

Salvietti, G., Gioioso, G., Malvezzi, M., & Prattichizzo, D. (2016). How to Map Human Hand Synergies onto Robotic Hands Using the SynGrasp Matlab Toolbox. In Human and Robot Hands: Sensorimotor Synergies to Bridge the Gap Between Neuroscience and Robotics (pp. 195-209). Springer International Publishing [10.1007/978-3-319-26706-7_12].

How to Map Human Hand Synergies onto Robotic Hands Using the SynGrasp Matlab Toolbox

SALVIETTI, GIONATA;GIOIOSO, GUIDO;MALVEZZI, MONICA;PRATTICHIZZO, DOMENICO
2016

Abstract

Throughout this book, we have described how neuroscientific findings on synergistic organization of human hand can be used to devise guidelines for the design and control of robotic and prosthetic hands as well as for sensing devices (see Chaps. 8, 10, 11 and 15). However, the development of novel robotic devices open issues on how to generalize the outcomes to different architectures. In this chapter, we describe a mapping strategy to transfer human hand synergies onto robotic hands with dissimilar kinematics. The algorithm is based on the definition of two virtual objects that are used to abstract from the specific structures of the hands. The proposed mapping strategy allows to overcame the problems in defining synergies for robotic hands computing PCA analysis over a grasp dataset obtained empirically closing the robot hand upon different objects. The developed mapping framework has been implemented using the SynGrasp Matlab toolbox. This tool includes functions for the definition of hand kinematic structure and of the contact points with a grasped object, the coupling between joints induced by a synergistic control, compliance at the contact, joint and actuator levels. Its analysis functions can be used to investigate the main grasp properties: controllable forces and object displacements, manipulability analysis, grasp quality measures. Furthermore, functions for the graphical representation of the hand, the object and the main analysis results are provided.
978-3-319-26705-0
Salvietti, G., Gioioso, G., Malvezzi, M., & Prattichizzo, D. (2016). How to Map Human Hand Synergies onto Robotic Hands Using the SynGrasp Matlab Toolbox. In Human and Robot Hands: Sensorimotor Synergies to Bridge the Gap Between Neuroscience and Robotics (pp. 195-209). Springer International Publishing [10.1007/978-3-319-26706-7_12].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11365/997746