The development of a grasp planner for multifingered robot hands is described. The planner is knowledge-based, selecting grasp postures by reasoning from symbolic information on target object geometry and the nature of the task. The ability of the planner to utilize task information is based on an attempt to mimic human grasping behavior. Several task attributes and a set of heuristics derived from observation of human motor skills are included in the system. The paper gives several examples of the reasoning of the system in selecting the appropriate grasp mode for spherical and cylindrical objects for different tasks.>

This paper presents an approach to synthesizing the control required by a dextrous multifingered robot hand to reach and safely grasp an arbitrary target object. The synthesis is based on analysis of the grasping task as performed by human beings. We divide the task into (1) a target approach phase (including target identification, hand structure and grasp mode selection, selection of approach trajectory, hand preshaping and orientation) and (2) a grasp execution phase (including shape and force adaptation). Each aspect of the required control is discussed. Particular attention is paid to the role of geometric modeling in target identification, to preshaping during the approach trajectory and to the requirements for autonomy in completion of the grasping task. The underlying philosophy is that of reflex control; each aspect of the grasping task is initiated and terminated using sensory data and rules of behavior derived from human expertise in such tasks. The contents and organization of the knowledge base which codifies this expertise are discussed. The fundamental assumptions upon which this control philosophy is based are identified throughout the paper. Preliminary results of a graphical simulation of hand preshaping are given.

This paper describes the principles of a new method of robot control which mimics the reflex control of human motion. The concept of an artificial or synthetic reflex arc is defined, using the biological reflex as reference. The view of reflex control as an "experiential expert system" is explained. Hardware and software elements necessary for the implementation of external reflex control are described, The set of artificial reflex arcs which can reproduce the desired functional motion is identified on the basis of singular events occurring during the execution of the the motion. Applications of the theory to control of knee and leg motion in rehabilitative robotics are discussed in detail.

The paper describes a procedure applicable to analog computers for obtaining the sensitivity function of dynamic systems to parameters that change the order of differential equations. The procedure developed is applied to a problem in error analysis and to a problem in steepest ascent model identification. For purposes of comparison, the sensitivity with respect to normal parameters is also presented.

Methods of practical solution of integral equations on electronic differential analyzers are not well developed. In those cases where such methods have been outlined, special and costly additional equipment is required. Results presented in this work show that practical solution of integral equations is possible using a repetitive differential analyzer of convenient design.

In previous papers a new technique for performing in a single electronic computing unit all nonlinear mathematical operations in a differential analyzer was described. The field of application of this technique is extended to include the generation of functions of several variables.