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.

A strategy for grasp synthesis with multifingered robot hands

The detection of the onset of motion and slip between an end effector and workpiece has been of interest for some time and many schemes have been proposed. This paper reviews some of the background on slip detection methods and proposes use of acoustic emission signal analysis a slip detection technique. The genesis acoustic emission during slip is discussed and experimental evidence presented to the sensitivity of acoustic emission to slip between two surfaces. Preliminary tests with a robot gripper have also done to demonstrate the feasibility of acoustic emission slip detector.

Slip detection using acoustic emission signal analysis

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.

Robot control by reflex actions

A manipulator having a grasping mechanism for grasping an object and an arm mechanism for lifting the grasped object, is disclosed. A weight detector is provided which detects a force that the top of the arm mechanism receives in the gravitational direction when the grasped object is being lifted. In order to find the minimum grasping force sufficient to lift the object, a grasp detector is provided for detecting, from the output of the weight detector, that the object cannot be lifted up with the present grasping force and a desired grasping force selector for selecting successively a desired value of grasping force starting from a predetermined minimum desired value until it is detected that the object is lifted. A grasping force control circuit controls the grasping force to the selected desired value.

Control system for grasping force of a manipulator for grasping objects

The purpose of this review and commentary is to examine the sense of touch in robots This includes a presentation of the history of this relatively new technology, examination of the present state-of-the-art, and discussion of future challenges and opportunities in tactile sensing for automata Special emphasis is placed on considerations relevant to industrial assembly robots

Z Stojiljkovi

Papers

Multifunctional terminal device with adaptive grasping force