For the trajectory following problem of a robot manipulator, a robust estimation and control scheme which requires only position measurements is proposed to guarantee uniform ultimate bounded stability under significant uncertainties and disturbances in the robot dynamics. The scheme combines a class of robust control laws with a robust estimator where the robust control law can be chosen to be either a modification of the standard computed torque control law or simply a linear and decentralized “PD” control law. The proposed robust estimator is also linear and decentralized for easy implementation. Constructive choices of the gains in the control law and estimator are proposed which depend only on the coefficients of a polynomial bounding function of the unknown dynamics. The asymptotic stability of the tracking errors and the estimation error is also investigated. Experimentation results verify the theoretical analysis.

Part II continues to develop a hyper-stability framework for presenting physical interpretations of dexterous motion controls, such as hybrid position/force, impedance, model-based adaptive, learning control and coordination. In all cases passivity induced by introduction of a quasi-natural potential plays a key role. In view of these considerations, the final section discusses the possibility of development of a nonlinear circuit theory based on feedback connections of hyper-stable blocks, which may give rise to a physical understanding of dexterous and skilled motions for nonlinear mechanical systems and, eventually lead to the design of intelligent functions implementable in robotic machines.

This paper treats, in a general way, the problem of mobile robot navigation in a totally unknown environment. The different aspects of this problem are dealt with one by one. We begin by introducing a simple method for perceiving and analyzing the robot's local environment based on a limited amount of distance information. Using this analysis as our base, we present a navigation algorithm containing different action modules; some of these actions use Fuzzy Logic. The results presented whether experimental or simulation show that our method is well adapted to this type of problem.

Present day robot systems are manufactured to perform within industry accepted tolerances. However, to use such systems for tasks requiring high precision, various methods of robot calibration are generally required. These procedures can improve the accuracy of a robot within a small volume of the robot's workspace. The objective of this paper is to demonstrate the use of a single camera 3D computer vision system as a position sensor in order to perform robot calibration. A vision feedback scheme, termed Vision-guided Robot Control (VRC), is described which can improve the accuracy of a robot in an on-line iterative manner. This system demonstrates the advantage that can be achieved by a Cartesian space robot control scheme when end effector position/orientation are actually sensed instead ofcalculated from the kinematic equations. The degree of accuracy is determined by setting a tolerance level for each of the six robot Cartesian space coordinates. In general, a small tolerance level requires a large number of iterations in order to position the end effector, and a large tolerance level requires fewer iterations. The viability of using a vision system for robot calibration is demonstrated by experimentally showing that the accuracy of a robot can be drastically improved. In addition, the vision system can also be used to determine the repeatability and accuracy of a robot in a simple, efficient, and quick manner. Experimental work with an IBM Electric Drive Robot (EDR) and the proposed vision system produced a 97 and a 145 fold improvement in the position and orientation accuracy of the robot, respectively.

The Space Station Alpha is the most significant international space project of this century and the largest international technology development project ever undertaken. The space robot manipulators will be a substantial part of the space station and will perform tasks such as assembly as well as maintenance of the station. Therefore the robot manipulators need a very sophisticated real-time control capability for gross and fine motions (i.e. compliant motions) during various operations. Moreover, the proposed dual-arm robot system servicing the Space Station requires automated motion coordination, synchronization of the arms, and controlled mechanical interaction with fixed and moving objects involved in various tasks.

Lately, there have been numerous applications of computer algebra to special functions used in the various field of science and engineering. In this paper, we consider an efficient algorithm which generates velocity Jacobians for any class of general serial link manipulators in a compact form throughout the effective use of frame transformations. Compared with conventional techniques, a marked improvement of that capability is found in computer algebra applications to one class of a seven-joint manipulator. Together with finding of explicit solutions for joint rates, closed form arm solutions for the desired position of the hand are presented by relating the rotational motion of the elbow to a geometry problem.

This paper presents a neural network based control strategy for the trajectory control of robot manipulators. The neural network learns the inverse dynamics of a robot manipulator without any a priori knowledge of the manipulator inertial parameters nor any a priori knowledge of the equation of dynamics. A two step feedback-error-learning process is proposed. Strategies for selection of the training trajectories and difficulties with on-line training are discussed.

In this paper we present the results obtained from the implementation of a robust position/force controller on a two-degree-of-freedom direct drive robot. The controller is based on the theoretical work presented in references 1 & 2, which guarantees Globally Uniformly Ultimately Bounded (GUUB) position tracking error and bounded force tracking error. The controller accomplishes this stability result in spite of robot model uncertainty and only requires; joint position and velocity measurements, end-effector force measurements, and bounds on the model parameters. Experimental results described in this paper serve to verify the theoretical claims.

Identification of inertia constants and joint frictions of a robot manipulator is achieved in situ, without dismantling operations, by means of specific test motions. The necessary estimation of actuating torques is carried out by measuring, with Hall effect transducers, the current absorbed by the motors which power the system. This identification is accomplished by using a precise methodological order adapted to a planar SCARA type manipulator with two degrees of freedom. The identification of friction laws underscores a hysteresis phenomenon of the dissipative torques. This indicates that friction doesn't result from a simple superposition of a dry friction law and a viscous damping law. The identification results were applied with success to implementation of optimized trajectories computed on the basis of a dynamic criterion. The effective minimization of the performance criterion along the optimized trajectories, according to the corresponding standard trajectories, was verified experimentally by evaluating the motor work and actuator torques.

We describe an approach that generates a complete b-rep description of a polyhedral object from (geometric primitives derived from) dense range images taken from multiple view-points. Our approach, starting from basic face models of visible surfaces of objects in each local view, matches certain geometric features, extracts rigid-body transformations that relate the local views, and incrementally merges the face models (in local views) into a global 3-dimensional b-rep description of the object. A convenient and effective termination criterion is designed to monitor the merging process. The emphasis is on the use of geometric constraints in building a complete 3-dimensional model of the object.

We have implemented this system in C, running on a SUN Sparcstation. The system, as presented, has been tested on face models derived from several synthetic and real range images and performs successfully with realistic noise levels.

This paper addresses a method of satisfactorily controlling the grasp of objects. Emphasis is placed on achieving the desired stiffness of a grasped object as accurately as possible, especially when the fingers have redundant joints. A model describing the relation between stiffness and force is derived. Based upon this model, a hierarchical control scheme of the grasp stiffness, called decentralized object stiffness control (DOSC) is proposed. DOSC is composed of a fingertip stiffness synthesis (FSS) algorithm and orthogonal stiffness decomposition control (OSDC). Employing the proposed FSS always achieves the desired grasp stiffness by solving the constrained least square problem. The computed fingertip stiffness is achieved by OSDC. It offers a feasible way of controlling the fingertip stiffness as well as maintaining the stability of the finger configuration by modulating the joint stiffness. The developed control method is implemented on a two-fingered planar robot hand one finger of which has a redundant joint. The effectiveness of the control method is confirmed experimentally.

A computational technique for designing a physically realizable robust dynamic gait for a planar biped robot is developed. Firstly, a feasible set of gaits was constructed to satisfy the periodicity of the biped locomotion. Then the concept of dynamic, stability margin is introduced based on the robustness of a gait with respect to the external disturbances. Using that margin, we can assess the robustness of each dynamic gait in the feasible set. It is found that the parameter, called foot strike time margin, representing the readiness of the foot strike has a close positive correlation with the dynamic stability margin. We obtain a robust gait with respect to the external disturbance by maximizing the foot strike time margin. The robustness of the optimal gait is confirmed by the behavior of the gait after application of linear impulse as well as by the examination of the largest eigenvalue at the perturbed state.

This paper proposes a new method of estimating the position and heading angle of a mobile robot moving on a fiat surface. The proposed localization method utilizes two passive beacons and a single rotating ultrasonic sensor. The passive beacons consist of two cylinders with different diameters and reflect the ultrasonic pulses coming from the sonar sensor mounted on the mobile robot. The sonar sensor, again, mounted on a pan-tilt device then receives the reflected pulses while scanning over a wide area. The geometric parameter set of beaconis acquired from the sonar scan data obtained at a single mobile robot location using a new data processing algorithm. The presented algorithm is especially suitable for processing the sonar scan data obtained by ultrasonic sensor with wide beam spread. From this parameter set, the position and heading angle of the mobile robot is determined directly. The performance and validity of the proposed method are evaluated using two beacons and a single sonar sensor attached at the pan-tilt device mounted on a mobile robot, named LCAR, in our laboratory.

After the enthusiasm for creating “intelligent robots” in the early 1980's, progress of robotics research in the past decade has not fulfilled our expectations but revealed various difficulties in understanding motor control by man and implementing intelligent functions in robotic machines. To regain the initiative in the development of intelligent machines, this paper first presents a critical review of the state of the art of robot control and points out the necessity for improving robot servo-loops in order to facilitate skilled and dexterious motions in robotic manipulators and mechanical hands. It is then shown that the introduction of a quasi-natural potential in Lagrange's formulation of robot dynamics gives rise to the design of hyperstable PID servo-loops, which establish global asymptotic stability of set-point control. The hyperstability theoretical framework is then applied to the design of control commands in various control problems, such as hybrid (position/force) control, impedance control, model-based adaptive control, and learning control. In all cases, the passivity concept of residual robot dynamics plays a vital role in conjunction with the concept of feedback connections of two hyperstable nonlinear or linear blocks.

This paper studies the static rigidity behaviour of a parallel manipulator with legs modelled as elastic members under axial loading. Structurally, a parallel module is more rigid compared to a serial module and is expected to take heavier payloads. Therefore, a guidance for design of such parallel manipulators is needed which leads to maximum rigidity over the workspace. In the present work, the authors propose the concept of the flexibility ellipsoid for a parallel system. Various scalar measures of rigidity are formulated on the basis of the proposed ellipsoid. An algorithm, involving multiple objective nonlinear programming technique, is implemented to decide upon some important design parameters of a generalised six degrees of freedom Stewart platform type parallel manipulator. It is observed that irrespective of the other parameters, parallel manipulators with the legs pairwise joined at the top platform possess the highest rigidity. Moreover, there exists certain kinematic dimensions for which the designed parallel system is completely free from all sorts of singularity.

The analysis of the gait mode is an important step for constructing a walking robot. In this study an optimal turning gait of a four-legged walking robot is proposed, which maximizes walking speed keeping walking stability larger than a certain required value. To obtain an optimal gait algorithm, for body trajectory of the robot, maximum walking speed, feasible gait modes and stability margin are analyzed for a quadruped walking robot designed in this study. The proposed gait is sufficiently flexible, as to permit crab walking, turning walking and a pure rotational walking about a robot's geometric center. The validity of the proposed gait algorithm is confirmed by many simulations.

The paper presents a meta-study of the kinematic, dynamic and electrical parameters for the PUMA 560 robot. Parameter values which have been reported in the literature are transformed into a single system of units and coordinates, and differences in the data and measurement techniques are discussed. New data have been gathered and are presented where the record was incomplete.

This paper presents a parametric study of automated vehicles using the sensitivity theory. A sixth order dynamic model of an axisymmetric vehicle is developed in the state space format to represent its 3 degrees-of-freedom motion in the lateral, yaw and roll modes. Variations of the important parameters of the vehicle are grouped into three separate vectors: with the elements consisting of inertia, stiffness and damping, and geometric-kinematic parameters respectively. The effect of every element of these vectors on the state variables is studied carefully, a comparison being made among the state variables to reveal the relative influence of the parameter-induced variations. This helps better understanding which mode of the system is more affected by changes in particular parameters and the severity in the transient response and in the steady-state response. Then the effects of a particular vector on the performance of the system is studied.