A computational technique for obtaining minimum-time trajectories for robot manipulators is described in this paper. In the analysis, limitations to link movements due to design constraints are taken into consideration. Numerical examples based on a two-link planar robot arm shows the feasibility of the technique proposed. A physical explanation for the general characteristics of the observed trajectories is also presented. The importance of appreciating optimal control issues in designing robot manipulators and in planning robot workstation layouts is emphasised.

The dynamics of sensors operated devices such as Automated Mobile Robots and more generally automated target seeking devices is studied in presence of noise. We introduce a simple and analytically tractable class of dynamics which permits to classify qualitatively and somehow quantitatively also the approach to the targets when fluctuations corrupt the ideal trajectories. Our model constitute a first evaluation of the feasibility of an efficient approach when the parameters of the model (statistics of the noise, lengths of the path and progressing steps and heading velocity) are known.

An algorithm is presented for the on-line generation of minimum-time trajectories for robot manipulators. The algorithm is designed for intelligent robots with advanced on-board sensory equipment which can provide the position and orientation of the end-effector. Planning is performed in the configuration (joint) space by the use of optimised combined polynomial splines, along with a search technique to identify the best minimum-time trajectory. The method proposed considers all physical and dynamical limitations inherent in the manipulator design, in addition to any geometric path constraints. Meeting the demands of the heavy computations involved lead to a distributed formulation on a multiprocessor system, for which an intelligent control unit has been created to supervise its proper and practical implementation. Simulation results of a proposed case study are presented for a PUMA 560 robot manipulator.

The problems concerning the control of constrained motion of manipulation robots are discussed in the paper. Two general problems of hybrid position/force control are considered: the problem of interaction between position and force control and the problem of contact between a robot and an environment. Some promising solutions to these problems are identified. It is shown that adaptive control is necessary to solve these problems. A new control scheme is proposed and results of computer simulations are presented

Today's industrial machines and manipulators have no capability to learn by experience. Performance and productivity could be greatly enhanced if a machine could modify its operation based on previous actions. This paper presents a learning control scheme that provides the ability for machines to utilize their past experiences. The objective is to have machines mimic the human learning process as closely as possible. A data base is formulated to provide the machine with experience. An optical infrared distance sensor is developed to inform the machine about objects in its working space. A learning control scheme is presented that utilizes the sensory information to enhance machine performance in the next trial. An adaptive scheme is proposed for the modification of learning gain matrices, and is implemented on an industrial robot. Experimental results verify the potentials of the proposed adaptive learning scheme, and illustrate how it can be used for improvement of different manufacturing processes.

Complex tasks that need to be performed through teleoperation led to the development of multifinger robot hands. A dextrous master is a multi-DOF controller which is worn by the operator in order to teleoperate these anthropomorphic hands. Force feedback is very useful when there is interaction with the environment. Providing force feedback to dextrous masters is an area of active research. We outline some of the human factors that influence the design of such masters. Of obvious importance is the hand geometry and the desired number of degrees of freedom. Additional criteria relate to the force perception of the hand. Finally, the man-machine impedance is of importance, since at the man/machine interface there are two impedances acting in series. One is the effective impedance of the human operator holding the master controller, the second is the impedance of the master controller being manipulated.

The extraction of contour information from subjects is essential for purposes of grasping and manipulation. We proposed that human haptic exploration of contours, in the absence of vision, would reveal specialized patterns, or “contour exploration procedures,” that are directly related to task goals and intrinsic system capacities. Our general assumptions, method, and initial results were described in Part 1. Part 2 provides an analysis of the relation between contour extraction procedures and processing constraints. These theoretical assumptions are supported by empirical findings, and implications are discussed for issues of importance to robotic exploration and manipulation.

This paper describes the development of assembly strategies based on hybrid force/position control. The assembly strategies developed are confined to the large class of assembly tasks defined as a peg-in-the-hole assembly having a plane of symmetry passing through the axis of insertion.

The basic idea to develop a robotic system for programmable assembly is presented. This system can currently operate controlled manipulators with minor modifications, i.e. if a force/torque sensor and proper software for hybrid control are provided.

The principles of writing assembly strategies are analysed and examples of more complex assembly tasks than the classic round peg-in-the-hole are discussed in detail.

Nonlinear couplings between the various joints of a robotic arm cause trouble in robot control. One possibility to overcome these difficulties is offered by the concept of nonlinear decoupling. The latter leads to independent linear SISO systems, each of them describing the movement of one joint. Thus, an application of control concepts for linear SISO systems is possible. However, at present such decoupling controls are computed from the mathematical model of the arm, the so-called drive equations, whereas actuator dynamics are considered only in a secondary way. In this paper the decoupling problem for robots is investigated by accounting also for the actuator dynamics from the very beginning. This results in decoupling laws requiring a complete state feedback, i.e. not only joint positions and velocities but also the states of the various actuators have to be used. Further, formulas are given which make the computation of those states unsuitable for direct measurements.

For efficient visual servoing of an “eye-in-hand” robot, the concepts of Augmented Image Space and Transformed Feature Space are presented in the paper. A formal definition of image features as functionals is given along with a technique to use defined image features for visual servoing. Compared with other known methods, the proposed concepts reduce the computational burden for visual feedback, and enhance the flexibility in describing the vision-based task. Simulations and real experiments demonstrate that the proposed concepts are useful and versatile tools for the industrial robot vision tasks, and thus the visual servoing problem can be dealt with more systematically.

This paper presents a general technique to model flexible components (mainly links and joints flexibilities are considered) of manipulator arms based on Castigliano's theorem of least work. The robotic arms flexibility properties are derived and represented by the matrix of compliance coefficients. Such expressions can be used to determine the errors due to the robotic tip deformations under the application of a set of applied loads at the tip in a Cartesian space. Once these deformations are computed, they may be used to correct for the positional errors arisen from the robotic structural deformations in the motion control algorithms.

A SCARA type direct-drive robot which can be used in the assembly operation of printed circuit boards was designed and manufactured with graphite fiber epoxy composite material. The optimum stacking angle of the graphite fiber which gives the minimum deflection of the composite robot arm was calculated by the energy method and the manufacturing method of the box-type cross section of the robot arm with composite materials was developed.

In order to compare the dynamic characteristics of the composite material robot arm with a conventional material robot arm, an aluminum robot arm which has the same dimensions and thickness of the composite robot arm was manufactured.

The static and dynamic characteristics of the composite material robot arm such as static deflection, natural frequency and damping as well as weight saving were considerably improved compared to those of the aluminum robot arm.

In this paper, an efficient method for computing the Jacobian matrix for robot manipulators on a single processor computer is developed. Compared with the existing methods, the number of required numerical operations is considerably smaller, making the proposed technique the fastest, or the least expensive, one for any general N degrees-of-freedom manipulator.

The paper presents an educational system for teaching and research in robotics which consists of a manipulator, controller and a PC compatible host computer. The advanced design of host-computer user-interface software makes the system very suitable for teaching. It allows the user not only to follow the system states but also to change the control structure on-line. In the first part of this paper the architecture of the system, window-oriented user interface, specially designed robot language and several build-in students lessons will be described as well as the data acquisition system and advanced graphical capabilities.

In the second part of this paper the executive controller architecture is described. Besides the manipulator control function and IO operations, the controller supports communication with the host-computer. The controller is programmable, i.e. it executes various tasks within user-defined and build-in students lessons. By the use of simple host-computer commands the controller can execute various algorithms both for trajectory generation and dynamically compensated digital servo control. The dynamic model components in the feed-forward and feed-back control loop can be selectively included and changed during the manipulator's motion. Experimental results with a 4-link educational robot are presented.