SCARA Type Robot Research Articles

Enhancement of positioning accuracy of industrial robots with a reconfigurable fine-positioning module

Abstract Conventional industrial robots achieve a high flexibility by low investment costs, but they are limited in absolute positioning accuracy. The costs for the introduction of a new special high precision robot for micro-handling are very high, where the workspace is limited to small areas. For handling operations, best results according velocity, precision and costs can be achieved with SCARA-type robots. Therefore, the introduction of a fine-positioning module for the enhancement of positioning accuracy of robots in the micro-handling techniques, become indispensable. The most micro-handling systems on the market have been designed for individual work-pieces. With our proposed fine-positioning module, we get a reconfigurable robot system for the execution of different handlings tasks both in the micro- and meso-scale 2 in the industrial automation. To increase the flexibility of the robot system, the handling system is equipped with a tool change system, which allows an automated couple of the fine-positioning module with the Scara Robot. At this robot system, the Scara Robot will be used for coarse movements, and the fine-positioning module for very accurate positioning tasks. The fine-positioning module is equipped with a microscope, which enables in combination with an image processing system relative positioning technique, object recognition and measurements simultaneously. Handling of micro-objects and measurements are the major operations, which can be executed by the fine-positioning module.

A Solution to the Accuracy/Robustness Dilemma in Impedance Control

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> It has been reported that, in impedance control, there exists a dilemma between impedance accuracy and robustness against modeling error. As a solution to this dilemma, an accurate and robust impedance control technique is developed based on internal model control structure and time-delay estimation: the former injects desired impedance and corrects modeling error, the latter estimates and compensates the nonlinear dynamics of robot manipulators. Owing to the simple structure, the proposed control is designed without requiring entire model computation or complex algorithms. In 2-DOF SCARA-type robot experiments, the accuracy and robustness of the proposed control are confirmed through comparisons with other competent controllers including impedance control with disturbance observer. </para>

An Adaptive Tracking Control for Robotic Manipulators based on RBFN

Neural networks are known as kinds of intelligent strategies since they have learning capability. There are various their applications from intelligent control fields; however, their applications have limits from the point that the stability of the intelligent control systems is not usually guaranteed. In this paper we propose an adaptive tracking control for robot manipulators using the radial basis function network (RBFN) that is a kind of neural networks. Adaptation laws for parameters of the RBFN are developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Filtered tracking errors between actual outputs and desired outputs are discussed in the sense of the uniformly ultimately boundedness(UUB). Additionally, it is also shown that parameters of the RBFN are bounded. Experimental results for a SCARA-type robot manipulator show that the proposed adaptive tracking controller is adaptable to the environment changes and is more robust than the conventional PID controller and the neuro-controller based on the multilayer perceptron.

DCT Basis Function Learning Control

In this paper, a basis function learning control is developed in away parallel to time domain learning control. Basis function approach aims to reduce the dimension and computation of learning gain matrices while maintaining minimal loss of tracking precision. Here, we transplant two learning gain matrices, the transpose and the partial isometry, from time domain learning control into basis function learning control. These two learning gain matrices have no ill-conditioned problems in matrix computation and ensure a monotonic decay of tracking error. The basis vector of discrete cosine transform (DCT) is chosen as basis function for its high energy compression ratio and energy preservation feature. Experiments on two joints of a SCARA type robot verify the effectiveness of the proposed approaches. A few DCT coefficients may meet learning control specification and tracking precision can be improved by increasing the number of the DCT coefficients.

A robust control with a neural network structure for uncertain robot manipulator

A robust position control with the bound function of neural network structure is proposed for uncertain robot manipulators. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, and etc. Therefore, uncertainties are often nonlinear and time-varying. The neural network structure presents the bound function and does not need the concave property of the bound function. The robust approach is to solve this problem as uncertainties are included in a model and the controller can achieve the desired properties in spite of the imperfect modeling. Simulation is performed to validate this law for four-axis SCARA type robot manipulator.

Model-Based Fuzzy Tracking Control of Two-Link Manipulators with Dual Actuators

This paper presents a model-based tracking controller design for two-link manipulators using a fuzzy state-feedback gain-scheduling approach. The control law is equivalent to the parallel distributed compensation (PDC) scheme. The challenge of the control problem is the highly nonlinear dynamics of the investigated dual actuators powered by air-pressure that affect the dynamics of the robot manipulator. For a class of serial manipulators, the SCARA-type robot manipulator, a nonlinear state-space model is formulated by the Newton-Euler equation of the manipulator arm coupled with a reduced model of the actuators. The state-space model is transformed into a Takagi-Sugeno fuzzy approximation using a linearization around a grid of equilibrium points. Based on this, a global tracking controller is designed as a fuzzy gain-scheduler of state-feedback gains. It is shown by simulation results that this controller is capable to handle the coupled nonlinearities among the actuators and the manipulator arm.

Combined force and visual control of an industrial robot

This work proposes control structures that efficiently combine force control with vision servo control of robot manipulators. Impedance controllers are considered which are based both on visual servoing and on physical or fictitious force feedback, the force and visual information being combined in the image space. Force and visual servo controllers included in extended hybrid control structures are also considered. The combination of both force and vision based control allows the tasks range of the robot to be extended to partially structured environments. The proposed controllers, implemented on an industrial SCARA-type robot, are tested in tasks involving physical and virtual contact with the environment.

Motion Planning Approach of a Multi-fingered Robot for Carton Folding Operation

The motion planning approach of a multi-fingered robot for carton flap folding operations has been newly developed. This approach considers the loci of the tool center point for carton flap folding operations. Also that considers the pushing or fixing points of the carton flap. This approach is calculated from the rotating angle for carton flap folding and the position of a robot finger tip in contact with the carton surface, using inverse kinematics. And this approach can be adapted to changes of a carton size or a folding position. When the carton flap is folded using this approach, the robot finger tip touches the carton surface without slipping and moves along circular continuous path. Therefore in case of the rectangular carton box folding, each robot finger moves in each 2.5-dimensional Cartesian frame. In this report, the proposed approach is verified using a prototype robot system. This system consists of two pairs of the robot fingers and rotating mechanism for carton paper. Each finger has a 3-DOF SCARA type robot and a 1-DOF linear motion system. The testing carton boxes can be folded to the desired shape.

Design of Discrete-Time Multivariable Adaptive Repetitive Control Systems

There exist many applications of repetitive control on the factory floor, such as industrial robots and machine tool systems. Since most of the existing repetitive control systems are based on the so-called internal model principle, the system needs to include the internal model of the repetitive reference signals, which is usually higher order model. So it is difficult to apply the adaptive pole placement control because the controller needs to be higher order and a large number of controller parameters need to be estimated online. In this paper we propose a design of adaptive repetitive control systems that are capable of arbitrary pole placement. The proposed controller is based on the two degrees of freedom controller with repetitive feed-forward and adaptive feedback controllers. The adaptive feedback controller is also able to reject unknown disturbances by estimating the internal model of the disturbances. The method is applied to a SCARA-type robot and its effectiveness is experimentally examined.

Robotized Flange Assembling with Line Scan Camera Control

The paper describes an intelligent manufacturing system which performs geometric control, manipulation and assembling circular flanges that arrive at high speed on a conveyor belt and are randomly positioned and oriented. The 2D image of incoming flanges is created from a number of line scans executed by a linear camera. A geometry inspection is carried out in real time based on visual measurements of the flange's holes. If the geometry test passed, the location data is transferred to a SCARA-type robot which mounts each of them on a 5-component assembly. A comparative performance analysis for two types of lighting devices is included in the paper.

A Mobile Agents Approach to Virtual Laboratories and Remote Supervision

This paper presents the use of adaptive mobile agents for remote operation, enabling real-time response in spite of the limitations of the communication channels in terms of time-delays, availability, and reliability. Autonomy of the mobile agents is achieved through high levels of intelligence including execution monitoring and error recovery. Potential applications range from traditional telerobotics to virtual laboratories where mobile agents act as representatives of users in scientific experiments. Practical results are presented in a scenario where a SCARA-type robot is remotely commanded through the Internet.

Local POE model for robot kinematic calibration

A robot kinematic calibration method based on the local frame representation of the product-of-exponentials (Local POE) formula is introduced. In this method, the twist coordinates of the joint axes are expressed in their respective local (body) frames. The advantages of this new approach are threefolds: (1) revolute and prismatic joints can be uniformly expressed in the twist coordinates based on the line geometry; (2) the twist coordinates of the joint axes can be set up with simple values because the local frames can be arbitrarily defined on the links; (3) the kinematic parameters described by the twist coordinates vary smoothly that makes the method robust and singularity-free. By assuming that the kinematic errors exist only in the relative initial poses of the consecutive link frames, the kinematic calibration models can be formulated in a simple and elegant way. The calibration process then becomes to re-define a set of new local link frames that are able to reflect the actual kinematics of the robot. This method can be applied to robot manipulators with generic open chain structures (serial or tree-typed). The simulation and experiment results on a 4-DOF SCARA type robot and a 5-DOF tree-typed modular robot have shown that the average positioning accuracy of the end-effector increases significantly after calibration.

Velocity workspace analysis for multiple arm robot systems

In this paper, the analysis of manipulability of robotic systems comprised of multiple cooperating arms is considered. Given bounds on the capabilities of joint actuators for each robot, the purpose of this study is to derive the bounds for task velocity achievable by the system. Since bounds on each joint velocity form a polytope in joint-velocity space and the task space velocity is connected with joint velocity through Jacobian matrices of each robot, the allowable task velocity space, i.e. velocity workspace, for multiple cooperating robot system is also represented as a polytope which is called manipulability polytope throughout this paper. Based on the fact that the boundaries of the manipulability polytope are mapped from the boundaries of allowable joint-velocity space, slack variables are introduced in order to transform given inequality constraint given on joint velocities into a set of normal linear equalities in which the unknowns of the equation are composed of the vertices of manipulability polytope, vectors spanning the null space of the Jacobian matrix, and the slack variables. Either redundant or nonredundant cooperating robot systems can be handled with the proposed technique. Several different application examples including simple SCARA-type robots as well as complex articulated robot manipulators are included, and, under the assumption of firm grip, it will be shown that the calculated manipulability polytope for cooperating robot system is actually the intersection of all the manipulability polytopes of every single robot which is hard to be derived through geometrical manipulation.

A Mobile Agents Approach to Virtual Laboratories: Enabling Remote Operation over the Internet

This paper presents the use of adaptive mobile agents for remote operation, enabling real-time response in spite of the characteristics of the communication channels, such as time-delays, availability, and reliability. Autonomy of the mobile agents is achieved through high levels of intelligence including execution monitoring and error recovery. Potential applications range from traditional telerobotics to virtual laboratories where mobile agents act as representatives of users in scientific experiments. Practical results are presented in a scenario where a SCARA-type robot is remotely commanded through the Internet.

Structuring of Merged Robot Vision and Automated Visual Inspection Tasks

The paper presents a number of structuring principles for the design of merged Robot Vision and Automated Visual Inspection applications, where robot controllers extended with machine vision units act as master devices over CAM workstations. Two main problems are discussed: first, the structured search of prototyped and non-prototyped objects, with the objectives of avoiding collisions and minimising the amount of image acquisition and processing and second, the design of task-dependent geometric measurements using high level Vision Tools like: linear or circular rulers and point, line or arc finders. The design principles are analysed for SCARA-type robots programmed in the V+ environment. Experimental results are included.

A fuzzy model for automated precision robot assembly of parts

The fuzzy logic theory is suitable for solving the vagueness, nonlinearity and complexity problems of an assembly process by implanting ’human reasoning and action’ in the automated devices. The aim of the paper is to develop a simple and fast fuzzy rule-based algorithm and to explore via simulation the possibility of its implementation for precision assembly of chamferless parts. The main contribution is a simple, fast and reliable fuzzy algorithm, ready for imbedding in the PLC of a SCARA type robot.

Gain adaptation in sliding mode control of robotic manipulators

In this paper, a novel scheme is proposed to adapt the gains of a sliding mode controller (SMC) so that the problems faced in its practical implementations as a motion controller are overcome. A Lyapunov function is selected for the design of the SMC and an MIT rule is used for gain adaptation. The criterion that is minimized for gain adaptation is selected as the sum of the squares of the control signal and the sliding surface function. This novel approach is tested on a scara-type robot manipulator. The experimental results presented prove its efficacy.

Neuro-sliding mode control of robot manipulators

In this paper, a synergistic combination of neural networks with sliding mode control (SMC) is proposed. As a result, the chattering is eliminated and error performance of SMC is improved. In such an approach, two parallel Neural Networks (NNs) are proposed to realize the SMC. The equivalent control and the collective control term of SMC are the outputs of the NNs. The weight adaptation of NNs are based on the SMC equations with using a gradient decent method to minimize the control and chattering while optimize the error performance. This novel approach is applied to control of a scara type robot manipulator and experimental results are given.

High Accuracy Positioning in SCARA-Type Robot by Sensor-based Decoupling Control

To compensate for the effects of coupling torque and load variations experienced in SCARA-type robots, we propose a new method of sensor-based decoupling control. In this method the plant is first nominalized with the use of a disturbance observer and then nonlinear feedback control is accomplished by this nominalized system based on information from acceleration sensors installed at the end of the robot hand. As a result of high-speed reciprocal motion with a payload of 10 kg mounted on the hand, we were able to achieve satisfactory decoupling using this method. Improvements were also made in steady-state characteristics. [S1087-1357(00)01201-6]

ロボット制御精度の定量的評価法の検討 （第２報） 軌跡制御におけるロボット工具先端精度の定量的推定

In the robot control, many factors such as the control accuracy of servo motors, stiffness of the arm mechanism and the performance of the control algorithm have influence to the total accuracy of robot motion. So it is necessary to evaluate quantitatively the total control accuracy under such influences. Especially, in the Continuous Path control the error of the tool point path becomes larger in proportion to the motion speed. In the previous first paper, Multivariate Root Mean Square criterion is proposed and applied to estimate quantitatively the control accuracy of the robot and examination of quantized velocity and sampling period is executed. In this report the method is applied to evaluate the control accuracy of tool point path in CP motion and an estimation formula to calculate the tool point error from the deviation of joint deviation is introduced. Experimental results of SCARA type robot in circular interpolation are shown.