More than 50 ‘Handy 1’ robotic aids are now in use that enable some handicapped people to feed themselveswithout assistance from a carer. The benefits of thisdevice include much greater control of the eating process by the user as well as the development of eating skills. The article describes the genesis of this device and its subsequent development and early evaluation.

Accurate modeling of robot dynamics is a prerequisite for the design of model-based control schemes and enhancement of the performance of the robot. The dynamic parameters associated with a pseudo-inertia matrix are often difficult to identify accurately because the inertia torques are small in comparison to gravity loadings, thus creating signal processing problem. The identification method presented in this paper utilizes a balancing mechanism which increases the estimation accuracy of the dynamic parameters. The balancing mechanism has the effect of amplifying the inertia-related torque signal by eliminating gravity loadings acting on the robot joints. A series of motion data were experimentally obtained through sequential test steps. By incorporating the measured information about joint torques, angular positions, velocities and accelerations the least square algorithm was used to identify the dynamic parameters. The estimated values were converted to those of the original robot model to obtain its dynamic model parameters. The identified robot dynamic model was shown to be accurate enough to predict the actual robot motions.

This paper considers some problems concerning the motion and the control of large robots. The problem arises when highly nonuniform motion is required. It results in too strong dynamic loads and the robot cannot operate successfully. The solution is found in the introduction of redundancy in the form of parallel degrees of freedom. Kinematics of such a system follows the distributed positioning concept. The control scheme is developed for a one-dimensional redundant robot.

Present study on industrial manipulator control either completely neglects structural flexibility or only considers manipulator link flexibility. Ignoring joint flexibility may cause significant errors in gross motion control if the joint elastic effect is predominant. This paper presents an effective control scheme which can compensate for the motion errors generated by simultaneous existence of both link and joint flexibility. The manipulator dynamics is formulated comprehensively by a superposition of two models, namely, an assumed modes of vibration model for links and a torsional spring model.for joints. Then, a nonlinear feedback rate servo control system is developed that compensates for the gross motion errors introduced by both joint elasticity and link flexibility. Motion simulation results show that the proposed formulation can effectively describe the dynamic behavior of a flexible-link, elastic-joint robot. They also verify that the proposed controller is robust in that it can satisfactorily suppress the manipulator end oscillations and yield an accurate gross motion.

This paper investigates the kinematics and motion of a human arm as a manipulator with seven degrees of freedom, and how to deal with the extra degree of freedom that exists. It proposes that a change of configuration be divided into a sequence of motions where each time one of the joints is locked. It then presents a general technique to solve inverse kinematic equations of the different reduced models that arise.

The problem of constructing a smooth path with respect to time through N given points in configuration space is considered. Two variants of an algorithm suggested by Paul are presented and evaluated. It is shown that the algorithms suggested in this paper yield in general considerable improvements in two respects: Firstly, the deviation of the resulting path from the given points is reduced markedly and secondly, the overall time needed for the movement is reduced significantly and consequently, is closer to the true minimum-time. The price to be paid for these improvements is a moderate increase of computation time allowing still online use of the algorithm.

Due to the complexity of teleoperation tasks, human operators figure in the teleoperator perception-decision-control loop. The operator needs an interactive system to handle the huge flow of data between himself and the teleoperator.

The scene represented by the robot and its environment is viewed by one or more cameras. However, the video image may be degraded in extreme environments (underwater, space, etc.) or simply inadequate (2-D image).

In this paper we describe the visual perception aids based of the scene, and more specifically how these are generated by the method we put forward. The system developed at the LRE superimposes a 3-D synthetic image onto the video picture, and animates the scene in real-time on the basis of sensor information feedback. The graphic image can be generated from models, if the objects are known, otherwise interactively, with the cooperation of the operator if the objects are completely unknown. Experiments show that these graphic aids improve the operator's performance in task execution.

A binary tactile image feature extraction algorithm using image primitive notation and perceptrons is presented. The basic image segments are defined as geometric factors by which the image structure is described so that effective feature values such as image shape, image size, perimeter and texture may be extracted on the basis of local image computation. The local property of the tactile image computation is evaluated by the concept called order of the perceptrons and based on this feature extraction algorithm, an efficient tactile image recognition system is realised.