Showing papers in "Journal of Intelligent and Robotic Systems in 1995"

Determination of the orientation workspace of parallel manipulators

Abstract: An important step during the design of a parallel manipulators is the determination of its workspace. For a 6-d.o.f. parallel manipulator workspace limitations are due to the bounded range of their linear actuators, mechanical limits on their passive joints and links interference. The computation of the workspace of a parallel manipulator is far more complex than for a serial link manipulator as its translation ability is dependent upon the orientation of the end-effector. We present in this paper an algorithm enabling to compute the possible rotation of the end-effector around a fixed point. This algorithm enables to take into account all the constraints limiting the workspace. Various examples are presented.

Overview of damped least-squares methods for inverse kinematics of robot manipulators

Abstract: In this paper, we present a tutorial report of the literature on the damped-least squares method which has been used for computing velocity inverse kinematics of robotic manipulators. This is a local optimization method that can prevent infeasible joint velocities near singular configurations by using a damping factor to control the norm of the joint velocity vector. However, the exactness of the inverse kinematic solution has to be sacrificed in order to achieve feasibility. The damping factor is an important parameter in this technique since it determines the trade-off between the accuracy and feasibility of the inverse kinematic solution. Various methods that have been proposed to compute an appropriate damping factor are described. Redundant manipulators, possessing extra degrees of freedom, afford more choice of inverse kinematic solutions than do non-redundant ones. The damped least-squares method has been used in conjunction with redundancy resolution schemes to compute feasible joint velocities for redundant arms while performing an additional subtask. We outline the different techniques that have been proposed to achieve this objective. In addition, we introduce an iterative method to compute the optimal damping factor for one of the redundancy resolution techniques.

The mechanical design of a seven-axes manipulator with kinematic isotropy

Abstract: Discussed in this paper are the issues underlying the mechanical design of a seven-axes isotropic manipulator. The kinematic design of this manipulator was made based on one main criterion, namely, accuracy. Thus, the main issue determining the underlying architecture, defined by its Hartenberg—Denavit (HD) parameters, was the optimization of its kinematic conditioning. This main criterion led not to one set of HD parameters, but rather to a manifold of these sets, which allowed the incorporation of further requirements, such as structural behavior, workspace considerations and functionality properties. These requirements in turn allowed the determination of the link shapes and the selection of actuators. The detailed mechanical design led to heuristic rules that helped in the decision-making process in defining issues such as link sub-assemblies and motor location along the joint axes.

Selection of features and evaluation of visual measurements during robotic visual servoing tasks

Abstract: This paper presents some of the computer vision techniques that were employed in order to automatically select features, measure features' displacements, and evaluate measurements during robotic visual servoing tasks. We experimented with a lot of different techniques, but the most robust proved to be the Sum-of-Squared Differences (SSD) optical flow technique. In addition, several techniques for the evaluation of the measurements are presented. One important characteristic of these techniques is that they can also be used for the selection of features for tracking in conjunction with several numerical criteria that guarantee the robustness of the servoing. These techniques are important aspects of our work since they can be used either on-line or off-line. An extension of the SSD measure to color images is presented and the results from the application of these techniques to real images are discussed. Finally, the derivation of depth maps through the controlled motion of the handeye system is outlined and the important role of the automatic feature selection algorithm in the accurate computation of the depth-related parameters is highlighted.

A mobile robot iconic position estimator using a radial laser scanner

Abstract: Position determination for a mobile robot is an important part of autonomous navigation. In many cases, dead reckoning is insufficient because it leads to large inaccuracies over time. Beacon- and landmark-based estimators require the emplacement of beacons and the presence of natural or man-made structure respectively in the environment. In this paper, we present a new algorithm for efficiently computing accurate position estimates based on a radially-scanning laser rangefinder that does not require structure in the environment. The algorithm employs a connected set of short line segments to approximate the shape of any environment and can easily be constructed by the rangefinder itself. We describe techniques for efficiently managing the environment map, matching the sensor data to the map, and computing the robot's position. We present accuracy and runtime results for our implementation.

Robust adaptive control of redundant manipulators

Abstract: This paper presents an adaptive scheme for the motion control of kinematically redundant manipulators. The proposed controller is very general and computationally efficient since it does not require knowledge of either the mathematical model or the parameter values of the robot dynamics, and is implemented without calculation of the robot inverse dynamics or inverse kinematic transformation. It is shown that the control strategy is globally stable in the presence of bounded disturbances, and that in the absence of disturbances the size of the residual tracking errors can be made arbitrarily small. The performance of the controller is illustrated through computer simulations with a nine degree-of-freedom (DOF) compound manipulator consisting of a relatively small, fast six-DOF manipulator mounted on a large three-DOF positioning device. These simulations demonstrate that the proposed scheme provides accurate and robust trajectory tracking and, moreover, permits the available redundancy to be utilized so that a high bandwidth response can be achieved over a large workspace.

Collision: Modeling, simulation and identification of robotic manipulators interacting with environments

Abstract: The performance of many robotic tasks depends greatly on their dynamic collision behavior. This article presents a simple method for modeling and simulating collision behavior in manipulators. The main goal in this task is to provide informative contact models. The proposed models encompasscollision attributes which comprise not only (local) contact surface properties but also structural properties of the environmental object and the manipulator. With this method, the entire dynamic and interactive motion of the manipulator with the environmental object can be simulated effectively. This is verified by our simulation results. To facilitate our investigation, a 2 DOF planar elbow manipulator with PD control is considered in the simulations as well as theoretical analysis. The simulation results are used to highlight the collision attributes which affect collision behavior and to study the effects of these attributes on the manipulator-work environment safety and performance. On the other hand, the reliable operation of intelligent robotic systems in unstructured environments requires the estimation of collision attributes before the prediction of the collision behavior can be completed. For this purpose, we introduce the notion ofcollision identification. The present paper introduces a framework for collision identification in robotic tasks. The proposed framework is based on Artificial Neural Networks (ANNs) and provides fast and relatively reliable identification of the collision attributes. The simulation results are used to generate training data for the set of ANNs. A modularized ANN-based architecture is also developed to reduce the training effort and to increase the accuracy of ANNs. The test results indicate the satisfactory performance of the proposed collision identification system.

Rigid model-based fuzzy control of flexible-joint manipulators

Abstract: This paper considers the application of fuzzy control to achieve global trajectory tracking and active damping of flexible-joint manipulators. A reasonable approach based on the combined computed torque control using rigid robot model and fuzzy control is suggested for flexible-joint manipulators. Sets of ‘four input variables — one output variable’ fuzzy control rules for each actuator respectively, are suggested for the perturbation control. The simulation results show that the transient performance and steady-state accuracy are near those of the feedback linearization approach. The simulation results with payload or joint stiffness variation for the single-link case are also shown to demonstrate the robustness of the control law.

Visual servoing in the task-function framework: A contour following task

Abstract: We describe an approach to contour following unknown objects using a handeye robotic system. Relevant and sufficient feature points providing optical flow data are extracted from the edges of the target object. The desired motion of the end-effector is computed with the objective of keeping the visual features always at the same target location in the image plane. A cartesian PD controller is used to perform the desired motion by the robot's end-effector. To address thecontrol issues, we take advantage of the unifying robot control theory stated in the literature as thetask-function approach [21]. To validate our approach, we restricted our experiments to motionless objects positioned in a plane parallel to the image plane: three degrees of freedom (two of translation, one of rotation) are thus controlled.

A neural network compensator for uncertainties in robotic assembly

Abstract: It is difficult to represent the nonlinear characteristics in the dynamics of robot manipulators by means of a mathematical model. An alternative approach of using a neural network to learn the parametric and unstructured uncertainties in robot manipulators is proposed. It is then embedded in the structure of a joint torque perturbation observer to compensate for uncertainties in the robot dynamic model. As the result, an accurate estimate of the joint reaction torque against the environment can be deduced. The approach is applied to monitor the insertion force during electronic components assembly using a SCARA robot. A true teaching signal of neural network for learning the model uncertainties is obtained. Furthermore, a special motion test is conducted to generate the required training data set. After learning, the neural network is capable of reproducing the training data. The generalizing ability of the network enables it to output the correct compensation signal for a trajectory which it has not been trained. With the proposed technique, it is possible to verify the success of component insertion in real time and avoid causing damages to the electronic components.

Quality of stabilization of robot interacting with dynamic environment

Abstract: In this paper the task of stabilizing programmed robot motion and its interaction with the environment is solved in a general form, taking into account the inaccuracies of robot and environment dynamics, as well as external perturbations. This task is solved under the constraints of robot motion, control input and interaction force. Under these conditions the estimates of transient responses by position and force are obtained and estimates of transient response time are given. Control laws which ensure the quality of robot stabilization are introduced. A description of the classes of stabilized motions and forces depending on the initial and external perturbations levels is given. The theoretical results presented in the paper are illustrated on a simulation example of a two-DOF manipulator.

An intelligent assembly robotic system based on Relative Pose measurements

Abstract: One of the major problems in realizing intelligent assembly robotic systems has been the difficulty of compensating for uncertain and erroneous situations. In particular, pose (position and orientation) uncertainties lead to a challenging problem. In this paper, we outline a Relative Pose-based Strategy for effective dynamic end-pont control of manipulators in uncertain environments. The introduced strategy imposes new requirements on the higher levels of the control. Besides appropriate planning, control and sensing strategies, an advanced supervision system architecture needs to be provided. In this paper, the fundamental issues relating to intelligent assembly robotic system design are briefly discussed and an overall control architecture is introduced. The lower portions of the proposed architecture, viz. the Execution and the Supervisory Levels are described in detail.

Task decoupling in robot manipulators

Abstract: Task decoupling in robotic manipulators implies that there is a subset of joints primarily responsible for the completion of a subset of the manipulator task. In this paper, we take a novel and general view of task decoupling in which we identify link subsystems primarily responsible for completion of a subset of the manipulator task components, which is not necessarily position or orientation. Our analysis leads to the discovery of other decoupled manipulator geometries never identified before, wherein the decoupled system is responsible for a subset of degress-of-freedom involving a hybrid combination of both position and orientation. Closed-form inverse kinematic solutions for these manipulator geometries are therefore guaranteed. Task decoupling also implied singularity decoupling wherein singularities of decoupled subsystems are equivalent to the manipulator singularities. The analysis leads to a novel and efficient method for identifying the singularities and solving the inverse kinematics problem of six-axes manipulators with decoupled geometries. The practicality of the concepts introduced is demonstrated through an industrial robot example involving a hybrid position and orientation decoupling.

On the comparison of AI and DAI based planning techniques for automated manufacturing systems

Abstract: This research has been motivated by the challenge to survey, summarize and compare traditional and distributed AI planning techniques derived for automated manufacturing systems, including CIM, FMS, robotic assemblies and intelligent robotic systems. All these methods are examined to identify their advantages and limitations when applied to solve a specific problem in an automated manufacturing environment.

Ultrasonic Navigation for a Wheeled Nonholonomic Vehicle

Abstract: In this paper, we demonstrate a reliable and robust system for localization of mobile robots in indoors environments which are relatively consistent to a priori known maps. Through the use of an Extended Kalman Filter combining dead-reckoning, ultrasonic, and infrared sensor data, estimation of the position and orientation of the robot is achieved. Based on a thresholding approach, unexpected obstacles can be detected and their motion predicted. Experimental results from implementation on our mobile robot, Nomad-200, are also presented.

Robot reachability problem: A nonlinear optimization approach

Abstract: The reachability of a robot manipulator to a target is defined as its ability to move its joints and links in free space in order for its hand to reach the given target. This paper presents a way of testing the reachability of a robot to given target. The target could be a three dimensional object represented by a cuboid, a line or merely a point.

Collision avoidance for a two-arm robot by reflex actions: Simulations and experimentations

Abstract: This paper addresses the problem of collision avoidance between the two arms of a two-arm robot. In our case, the problem is solved through the reflex action theory. In fact, one arm is protected by virtual protection zones. When an unscheduled event occurs, in other words when the second arm is going to collide with the first one, the shape of the protection zones is modified. Then, a motion is computed for the first arm to rebuild the initial shape of the protection zones. The use of different shapes for the protection zones is explained and justified. Several strategies to compute the motion are proposed and discussed. Finally, this method is tested in simulation and on real experiments for different kinds of two-arm robots: planar manipulators, PUMA 560 robots and parallelogram robots.

Real-time shared control system for space telerobotics

Abstract: The shared control system is a modular real-time system designed to execute complex tasks through the intelligent coordination of task modules. A state machine is used to control task sequencing, and due to the automatic switching, the accuracy and reliability with which tasks are executed, is greatly improved. Tasks consist of sets of independent, modular, and reusable subtasks whose outputs are combined to create the control. This system has proved itself useful for rapid development of reliable high level multiple sensor based manipulation and control tasks. Additionally, we have integrated a neural network based visual servoing system, a semi-compliant Cartesian trajectory following heuristics, and a real-time graphical user interface in the system. The shared control system was implemented for the Self-Mobile Space Manipulator (SM 2) to handle a range of tasks associated with locomotion, manipulation, and material transportation on Space-Station Freedom.

Aimy: An autonomous mobile robot navigation in unknown environment with infrared detector system

Abstract: Aimy — an Autonomous Mobile Robot (AMR), capable of moving in an unknown environment filled with obstacles, has been developed. To avoid collision with unexpected obstacles, an Infrared Detector System (IDS) for providing multiple reading data was designed and implemented. A navigation/obstacle avoidance strategy for a mobile robot, which is based on the use of infrared detector data only, is discussed. Experiment results are also presented which exhibit the power of the developed algorithm and Infrared Detector System.

A sensing strategy for the reverse engineering of machined parts

Abstract: The reverse engineering of machined parts requires sensing an existing part and producing a design (and perhaps a manufacturing process) for it. We have developed a reverse engineering system that has proven effective with a set of machined parts. This paper describes the system, presents some results, and discusses strategy for a new system.

Dynamic Motion Planning using a distributed representation

Abstract: Methods for dynamic motion planning are presented which take into account not only geometric environmental constraints but also physical constraints on motion. The approach uses a distributed representation which allows parallel implementation of the using a cellular strength-diffusion method in the search for the motion in space-time. We consider three cases: (1) no knowledge of the motion of the obstacles is assumed so that the planning is purely reactive; (2) full knowledge of the moving obstacles is available so that the planner can deliver an optimal motion; and (3) an interleaved algorithm in which the ability to predict a short time ahead (based on an assumption of simple linear motion of the obstacles) is exploited. This last algorithm emphasizes the importance of the interaction between the planner and the environment via sensors. We conclude that to plan motion in a dynamic environment in which uncertainties abound, the only sensible strategy is to constantly sense the world and plan the motion accordingly.

Tracking control of mechanical systems via sliding Lagrangian

Abstract: According to a classical theorem in mathematical physics, a mechanical system is completely defined by its Lagrangian. This property is utilized to design the tracking control of manipulators via a new family of sliding surfaces referred to as ‘sliding Lagrangian surfaces’ and which exhibit some interesting features. They are physically meaningful. They create forces of reaction of low magnitude. They are intimately related to the second variation of the mechanical Lagrangian, in such a manner that one can refine the design by using a neighbouring-optimal control involving linear dynamic and quadratic cost. One can also combine the approach with the variable structure technique to achieve a good robustness with a low chattering phenomenon.

Controllers with diagnostic capabilities. A neural network implementation

Abstract: Designing controllers with diagnostic capabilities is important as in a feedback control system, detection and isolation of failures is generally affected by the particular control law used. Therefore, a common approach to control and failure diagnosis problems has significant merit. Controllers capable of performing failure diagnosis have additional diagnostic outputs to detect and isolate sensor and actuator faults. A linear such controller is usually called a four-parameter controller. Neural networks have proved to be a very powerful tool in the control systems area, where they have been used in the modelling and control of dynamical systems. In this paper, a neural network model of a controller with diagnostic capabilities (CDC) is presented for the first time. This nonlinear neural controller is trained to operate as a traditional controller, while at the same time it provides reproduction of the failure occurring either at the actuator or the sensor. The cases of actuator and sensor failure are studied independently. The validity of the results is verified by extensive simulations.

Coloured object recognition using invariant spectral features

Abstract: A new algorithm using invariant spectral features for segmenting colour images is presented in this paper. Input data are three primary images obtained from a colour sensor. The input colour image is transformed to IHS (Intensity, Hue, Saturation) colour space. This colour space transform compensates for illumination variations and delivers image pixel values with low variance for individual colour regions, hence contributing to simplified segmentation. The hue and saturation images are then separately filtered and combined. The resulting image is segmented by means of a threshold process. An opening operation on the segmented image completes the algorithm. Experimental results obtained for several images are presented. Issues related to illumination and sensors are also addressed.

Minimum-time control for an inverted pendulum under force constraints

Abstract: In order to numerically solve the minimum-time control problem of a linear system, the system is usually discretized with a fixed sampling period. Then the minimum count of control steps is searched to meet the constraints of the final state and the input variables. Since the count is a variable, there is no direct way for handling such problems except by exhaustive iteration. In contrast to the traditional methods, a new numerical technique was developed recently to avoid the exhaustive iteration. In this method, the control step is fixed and the sampling period is treated as a variable. Since this method requires only two iterations, it will reduce the computation time significantly. This paper applies this new numerical technique to generate the minimum-time trajectory between two end-points for an inverted pendulum under force constraints. Two main issues are addressed. The first one is the problem formulation in discrete-time domain and the second one is the generation of feasible solutions for the global search. Simulation examples are included for illustration.

Regulation of Unknown Nonlinear Dynamical Systems via Dynamical Neural Networks

Abstract: In this paper, we are dealing with the problem of regulating unknown nonlinear dynamical systems. First a dynamical neural network identifier is employed to perform ‘black box’ identification and then a regular static feedback is developed to regulate the unknown system to zero. Not all the plant states are assumed to be available for measurement.

A comparison of methods for the control of redundantly-actuated robotic systems

Abstract: Mechanical hands, legged vehicles and cooperating manipulators are robotic systems containing closed kinematic chains which are typically driven by more actuators than required. As a result, the force distribution existing in these systems cannot be determined simply from the governing rigid-body statics or dynamics equations since these equations are underdetermined. Techniques have been proposed to overcome this obstacle — the most common being to formulate an optimization problem whose solution will be a force distribution which is optimal in a prescribed sense. A second approach which has been suggested is one in which the elasticity of the constituent bodies is considered in order to render the force-distribution problem determinate, in a manner analogous to the techniques typically used in structural mechanics to analyze hyperstatic structures. A third approach would be to deactivate certain actuators in order to reduce the number of unknowns so that the problem becomes determinate. In the present paper, these methods are compared and the first is shown to yield the best results.

Robotic eye-in-hand calibration by calibrating optical axis and target pattern

Abstract: Robotic eye-in-hand configuration is very useful in many applications. Essential in the use of this configuration is robotic hand-eye calibration. The method proposed in this paper, calibrating the optical axis of the camera and a target pattern, creates an environment for camera calibration without using additional equipment. By using the geometric relation between the optical axis and the robot hand, calibration of the optical axis and the target pattern becomes a feasible process. The proposed method requires identification of the points intersected by the optical axis with the target pattern. Image-processing techniques for identifying these intersection points are developed and implemented by designing the target pattern with a checkerboard pattern. The accuracy issue of the proposed method is discussed. Finally, experimental results are presented to verify the proposed method.

Calculation of Repeatable Control Strategies for Kinematically Redundant Manipulators

Abstract: A kinematically redundant manipulator is a robotic system that has more than the minimum number of degrees of freedom that are required for a specified task. Due to this additional freedom, control strategies may yield solutions which are not repeatable in the sense that the manipulator may not return to its initial joint configuration for closed end-effector paths. This paper compares two methods for choosing repeatable control strategies which minimize their distance from a nonrepeatable inverse with desirable properties. The first method minimizes the integral norm of the difference of the desired inverse and a repeatable inverse while the second method minimizes the distance of the null vectors associated with the desired and the repeatable inverses. It is then shown how the two techniques can be combined in order to obtain the advantages of both methods. As an illustrative example the pseudoinverse is approximated in a region of the joint space for a seven-degree-of-freedom manipulator.

A plan-generating systems constructor for cooperative application domains

Abstract: MAP is a system which helps to design task-level actions of an intelligent robot system and to test the automatic generation of plans. The attention is mainly focused on cooperative application domains; in this way, our system is able to construct plans involving several agents, by specifying which actions can be executed simultaneously. MAP is mainly written in SmallTalk; however, we make use of Prolog for generating plans.