Robot Grasp Synthesis Algorithms: A Survey

This article presents a survey of the existing computational algorithms meant for achieving four important properties in autonomous multifingered robotic hands. The four properties are: dexterity, equilibrium, stability, and dynamic behavior The multifingered robotic hands must be controlled so as to possess these properties and hence be able to autonomously perform complex tasks in a way similar to human hands. Existing algorithms to achieve dexterity primarily involve solving an unconstrained linear programming problem where an objective function can be chosen to represent one or more of the currently known dexterity measures. Algorithms to achieve equilibrium also constitute solving a linear program ming problem wherein the positivity, friction, and joint torque constraints of all fingers are accounted for while optimizing the internal grasping forces. Stability algorithms aim at achiev ing positive definite grasp impedance matrices by solving for the required fingertip impedances. This problem reduces to a nonlinear programming problem. Dynamic behavior algorithms determine fingertip impedances, which, when achieved, lead to a desired dynamic behavior. This pr