We describe an approach for planning grasps of multifingered robot hands based on a small vibration model. Using features of the grasp configuration, we analyze asymptotic stability, contact situations, and uniaxial fingertip force constraints for the combined planning of finger posture and finger position, and characterize the generalized mass, damping, and stiffness. Choosing the largest time constant of the vibration model as an optimization criterion for planning finger postures and positions, the original problem of dynamic grasp planning is formulated as a nonlinear program. Simulation examples for a three-fingered robot hand grasping a spherical object demonstrate the effectiveness of the approach.

To realize the control of redundant manipulators, the concept of the motion optimizability measure is introduced. We derive an analytical solution technique for the inverse kinematics of a redundant robot that reduces the computational complexity and does not require the pseudoinverse Jacobian. Based on this technique, we propose an efficient, kinematic optimal control scheme. We show how to incorporate multiple criteria in the formulation. An online implementation of the system that ensures stable operation is presented.>

This research concerns the relationship between distance accuracy and positioning accuracy for robotic manipulators. We propose an approach for calibration and verification of the positioning accuracy based on a polynomial approximation to the workspace. Utilizing singular value decomposition a method is developed for distance error compensation. Computed results show that the distance accuracy and positioning accuracy of the robot can be improved by use of the proposed technique. The technique is illustrated for a PUMA 560 industrial robot.>

The grasping stiffness and the contacting stiffness for the grasping system of a multifingered robot hand are characterized. Using a Lagrangian formulation, the authors develop the small displacement vibration equation of the grasping system. Based on the features of a grasping state, they characterize object stability, contact stability, contact position, and uniaxial fingertip force constraints for grasp planning. From the asymptotical stability of the vibration system, a quality measure is defined that is used as an objective for grasp planning, and grasp planning is formulated as a nonlinear programming problem. An example for a three-fingered robot hand grasping a spherical object demonstrates the applicability and effectiveness of this approach. Numerical results using a constrained conjugate direction descent technique are described.>

Robotic systems have advantages for recovery and identifiation of objects in hazardom environments. Under such conditions it may be impractical to use visual, acoustic or electromagnetic sensors for detection. At the Center for Robotics and Manufacturing Systems of the University of Kentucky, a three-fingered dextrous hand is being integrated with 3-0 tactile data acquisition and pattern recognition to develop the Tactile Object acquisition and Correlation Hand (TOUCH) system. We describe the 3-0 data acquisition algorithms for determining finger-tip positioning patterns and sampling 3-0 coordinutes of the object by sensing forces at the finger-tips. The result of this sampling is a 3-0 polyhedron enclosing the touched object. A second function of thepositioningpatterns is to acquire mass features while grasping and moving the object.

A fast and simple algorithm for determining optimal grasps of a planar multifingered robotic hand is presented. Using a representation for the stiffness of a planar grasp system, the authors derive conditions for static equilibrium, task-oriented grasping, and stability. An optimization model for determining optimal grasps of a planar multifingered hand is established using a quality measure which includes the effect of the external disturbing forces and moments. A constrained gradient descent technique is used to compute the optimal grasps. An example demonstrates the applicability and effectiveness of the theory.>

A fingertip force decomposition model for a multifingered robot hand grasping and manipulating an object is proposed. During the trajectory execution the fingertip force is decomposed into a dynamic equilibrating force and an internal interaction force. Using the equations of motion and the displacement consistency relationship of the virtual grasping system, a computational algorithm is derived for the dynamic equilibrating forces subject to the constraint of dynamic stability. To simplify the formulation, a representation of the internal interaction force components is developed. An objective function based on the fingertip forces is defined and the internal interaction forces are optimally determined. A computational algorithm for planning fingertip forces during trajectory execution is derived.>