TY - GEN
T1 - Force optimization approaches for common anthropomorphic grasps
AU - Cloutier, Aimee
AU - Yang, James
N1 - Publisher Copyright:
Copyright © 2016 by ASME.
PY - 2016
Y1 - 2016
N2 - A smart choice of contact forces between robotic grasping devices and objects is important for achieving a balanced grasp. Too little applied force may cause an object to slip or be dropped, and too much applied force may cause damage to delicate objects. Prior methods of grasping force optimization in literature have mostly assumed grasp only at the fingertips but have rarely considered how the whole hand grasps more common to anthropomorphic hands affect the optimization of grasping forces. Further, although numerical examples of grasping force optimization methods are routinely provided, it is often difficult to compare the performance of separate methods when they are evaluated using different parameters, such as the type of grasping device, the object grasped, and the contact model, among other factors. This paper presents three optimization approaches (linear, nonlinear, and nonlinear with linear matrix inequality (LMI) friction constraints) which are compared for an anthropomorphic hand. Numerical examples are provided for three types of grasp commonly performed by the human hand (cylindrical grasp, tip grasp, and tripod grasp) using both soft finger contact and point contact with friction models. Contact points between the hand and the object are predetermined. Results are compared based on their accuracy, computational efficiency, and other various benefits and drawbacks unique to each method. Future work will extend the problem of grasping force optimization to include consideration for variable forces and object manipulation.
AB - A smart choice of contact forces between robotic grasping devices and objects is important for achieving a balanced grasp. Too little applied force may cause an object to slip or be dropped, and too much applied force may cause damage to delicate objects. Prior methods of grasping force optimization in literature have mostly assumed grasp only at the fingertips but have rarely considered how the whole hand grasps more common to anthropomorphic hands affect the optimization of grasping forces. Further, although numerical examples of grasping force optimization methods are routinely provided, it is often difficult to compare the performance of separate methods when they are evaluated using different parameters, such as the type of grasping device, the object grasped, and the contact model, among other factors. This paper presents three optimization approaches (linear, nonlinear, and nonlinear with linear matrix inequality (LMI) friction constraints) which are compared for an anthropomorphic hand. Numerical examples are provided for three types of grasp commonly performed by the human hand (cylindrical grasp, tip grasp, and tripod grasp) using both soft finger contact and point contact with friction models. Contact points between the hand and the object are predetermined. Results are compared based on their accuracy, computational efficiency, and other various benefits and drawbacks unique to each method. Future work will extend the problem of grasping force optimization to include consideration for variable forces and object manipulation.
KW - Anthropomorphic hand
KW - Grasping force optimization
KW - Karmarkar's method
KW - Linear matrix inequalities
UR - http://www.scopus.com/inward/record.url?scp=85007618921&partnerID=8YFLogxK
U2 - 10.1115/DETC2016-60346
DO - 10.1115/DETC2016-60346
M3 - Conference contribution
AN - SCOPUS:85007618921
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 36th Computers and Information in Engineering Conference
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2016
Y2 - 21 August 2016 through 24 August 2016
ER -