Articulated Robot Manipulator Research Articles

A Practical Adaptive Sliding-Mode Control for Extended Trajectory-Tracking of Articulated Robot Manipulators

This paper presents a practical adaptive sliding-mode control (PASMC) scheme and then applies it to an articulated robot manipulator. An adaptive law is newly-developed in the adaptive sliding-mode control scheme, which is designed to be based on the magnitude of the time-varying switching gains, the sliding variables, and their derivatives. It aims to provide fast and stable adaptation rate without the undesirable side effects while in operation. Besides, since it is only in need of one gain parameter, the proposed control algorithm offers outstanding advantage in producing convenience of use to practicing engineers while reducing the time-consuming tasks, including the tuning process of parameters. Next, the proposed PASMC scheme produces two-type pole-placement approach that can attain the tunable dominant poles depending on whether the sliding variables remain in the vicinity of the sliding manifold. It helps to improve the convergence rate without over-estimated switching gains near the equilibrium point. Finally, the proposed one uses one-sample delayed information to cancel out system uncertainties and nonlinearities so that it may provide simple and compact control structure. From these benefits, the proposed control scheme offers synergistic effects, including effectiveness and practicality. The system stability is proved to be uniformly ultimately bounded by Lyapunov stability. The performance of the proposed control scheme is illustrated through experiments on a real robot manipulator, which is compared with that of the existing control schemes.

Bluetooth Controlled 5 Axis Articulated Robot Manipulator with Adaptive Gripper

In this paper discuss about the design and fabrication of 5 axis articulated robot manipulator. In this manipulator TRRTR configuration is used with 6 degree of freedom. By using this configuration each point in the work volume can be achieved accurately. A unique advantage in this design we can orient the object after picking the object. This manipulator controlled by Bluetooth plus USB 16 servo controller module by giving the control signal from PC using USB servo controller software. This robotic manipulator is capable of either taking up programs for angular motion using servo motors or it can be controlled manually by providing individual angular motion signal for every motor through Bluetooth. The programs are fed to do repeated sequential jobs while manual control can override the program in necessary situations. It is used as a human hand when human hand cannot perform at crucial situation.

Optimization of Energy Consumption in KUKA KR 16 Articulated Robot Manipulator

A study for optimal energy consumption in KUKA KR 16 articulated robot for pick-and-place task was introduce in this paper. In order to achieve the optimal energy consumption, an improve trajectory planning is required. Essentially, trajectory planning encompasses path planning in addition to planning how to move based on velocity, time and kinematics. Trajectory planning gives a path from a starting to a goal point by avoiding collisions in a 2D or 3D space. Therefore, this paper is focus on analyze the PTP motion and Linear motion in order to determine which is the best motion that can improve the trajectory planning. The optimal energy consumption to minimizing the movement based on three main axes where it used a big motors used to drive the axes. This method is much simpler in terms of development process and did not require any additional hardware to be install to the robot’s system. KUKA KR 16 is use to study optimal energy consumption and analyze PTP and Linear motion. The energy performance is measures with respect to two categories of movements known as Default and Optimal movement which do the same task repetitively within specific time. The result show that PTP motion consumed 6% more energy than Linear motion but completed 773 cycles within one hour whereas Linear motion only completed 492 cycles. Energy performance between Default and Optimal movement shows that Optimal movement recorded 21.8% less energy usage when compared to Default movement although the total cycles completed for both movement almost the same.

Dynamic Modeling of Three Links Robot Manipulator (Open Chain) with Spherical Wrist

Dynamic modeling of a robot manipulator is a central problem in an accurate robot control. In this paper; the dynamic equations of motion were derived by using Eular-Lagrange method for a six degree of freedom articulated robot manipulator based on the geometrical jacobian construction for each link and actuator. In addition, friction effects beside the end effector forces that act the environment are considered. A Matlab Simulink plant is developed to embrace the theoretical work and simulate the dynamic response for a designed nonlinear controller Proportional Derivative plus Gravity (PD+G), also a modified controller is applied to reject the disturbances and the internal friction effect where the settling errors were 3.57E-6, 2.09E-7, -3.63E-6, 8.84E-6, -5.39E-8 and -4.39E-5 (deg) for joints one to six respectively. The presented approach can be applicable to solve the dynamic problem of other n-link robot manipulators and achieve a suitable solution for tracking trajectories.

A posture measurement approach for an articulated manipulator by RGB-D cameras

The objective of this article aims at the safety problems where robots and operators are highly coupled in a working space. A method to model an articulated robot manipulator by cylindrical geometries based on partial cloud points is proposed in this article. Firstly, images with point cloud data containing the posture of a robot with five resolution links are captured by a pair of RGB-D cameras. Secondly, the process of point cloud clustering and Gaussian noise filtering is applied to the images to separate the point cloud data of three links from the combined images. Thirdly, an ideal cylindrical model fits the processed point cloud data are segmented by the random sample consensus method such that three joint angles corresponding to three major links are computed. The original method for calculating the normal vector of point cloud data is the cylindrical model segmentation method, but the accuracy of posture measurement is low when the point cloud data is incomplete. To solve this problem, a principal axis compensation method is proposed, which is not affected by number of point cloud cluster data. The original method and the proposed method are used to estimate the three joint angular of the manipulator system in experiments. Experimental results show that the average error is reduced by 27.97%, and the sample standard deviation of the error is reduced by 54.21% compared with the original method for posture measurement. The proposed method is 0.971 piece/s slower than the original method in terms of the image processing velocity. But the proposed method is still feasible, and the purpose of posture measurement is achieved.

Adaptive task-space control of robot manipulators using the Fourier series expansion without task-space velocity measurements

Many control approaches presented in the field of robotics require velocity signals, which are not usually provided by many commercial robots. The novelty of this paper is designing an adaptive model-free observer for robot manipulators in the task-space without the use of task-space velocity measurements. To compensate for the uncertainties and nonlinearities in the observer and controller, the Fourier series are utilized. Using Lyapunov stability theorem and Barbalat’s lemma, it is guaranteed that the tracking error and also the observer estimation error converge to zero. The case study is an articulated robot manipulator driven by permanent magnet DC motors. Simulation results and comparison with an extended state observer and linear observer verify the effectiveness of the proposed algorithm.

Tracking Error Constrained Super-twisting Sliding Mode Control for Robotic Systems

In this paper, we address a robust super-twisting sliding mode control that ensures finite-time convergence and the prescribed tracking error constrained performance of a robotic system. A tracking error-transformed variable based on a super-twisting sliding mode surface is constructed for achieving the transient and steady-state time performances of the position of the robotic manipulator, and satisfying the properties of an ordinary sliding mode control. The proposed controller performs the constrained positioning of the robot manipulator without using a complex modeling process or intelligent nonlinear approximations for unknown robot dynamics and uncertainty. The problem of difficult separation of an unknown nonlinear function into known and unknown parts in the conventional variable super-twisting algorithm (STA) is overcome by designing a convenient adaptive law for the unknown function. Thus, the proposed control approach provides both finite-time convergence and constrained tracking error boundedness within a prescribed position range of the robotic manipulator. The effectiveness of the proposed robust control scheme is demonstrated through its experimental application to an industrial articulated robot manipulator and a XY robotic manipulator.

Direct Adaptive Function Approximation Techniques Based Control of Robot Manipulators

In this paper, a simple model-free controller for electrically driven robot manipulators is presented using function approximation techniques (FAT) such as Legendre polynomials (LP) and Fourier series (FS). According to the orthogonal functions theorem, LP and FS can approximate nonlinear functions with an arbitrary small approximation error. From this point of view, they are similar to fuzzy systems and can be used as controller to approximate the ideal control law. In comparison with fuzzy systems and neural networks, LP and FS are simpler and less computational. Moreover, there are very few tuning parameters in LP and FS. Consequently, the proposed controller is less computational in comparison with fuzzy and neural controllers. The case study is an articulated robot manipulator driven by permanent magnet direct current (DC) motors. Simulation results verify the effectiveness of the proposed control approach and its superiority over neuro-fuzzy controllers.

Finite-time sliding surface constrained control for a robot manipulator with an unknown deadzone and disturbance

This paper presents finite-time sliding mode control (FSMC) with predefined constraints for the tracking error and sliding surface in order to obtain robust positioning of a robot manipulator with input nonlinearity due to an unknown deadzone and external disturbance. An assumed model feedforward FSMC was designed to avoid tedious identification procedures for the manipulator parameters and to obtain a fast response time. Two constraint switching control functions based on the tracking error and finite-time sliding surface were added to the FSMC to guarantee the predefined tracking performance despite the presence of an unknown deadzone and disturbance. The tracking error due to the deadzone and disturbance can be suppressed within the predefined error boundary simply by tuning the gain value of the constraint switching function and without the addition of an extra compensator. Therefore, the designed constraint controller has a simpler structure than conventional transformed error constraint methods and the sliding surface constraint scheme can also indirectly guarantee the tracking error constraint while being more stable than the tracking error constraint control. A simulation and experiment were performed on an articulated robot manipulator to validate the proposed control schemes.

Field programmable gate array–based servo control integrated chip for a six-axis articulated robot manipulator

The objective of this article is to build a field programmable gate array–based six-axis servo control integrated chip which can integrate the function of a motion trajectory planning and the function of six position/speed/current servo controllers into one integrated chip. In the work, first, a mathematical modeling of a robot manipulator with the actuator using permanent magnet synchronous motor is derived. Second, the proportional controller in the position loop, a proportional–integral controller in the speed loop and a vector controller in the current loop for each axis are applied. Third, a system on a programmable chip) technology which comprises an Altera field programmable gate array chip and an embedded soft-core Nios-II processor is considered to develop the proposed servo control integrated chip. However, in the servo control integrated chip, it has two modules. The first module is an embedded soft-core Nios-II processor which is used to generate the motion trajectory planning by software. The second module presents a six-axis servo controller intellectual property by hardware which is applied to execute six position/speed/current controllers. Therefore, the function of a motion trajectory command and the function of six position/speed/current servo controllers for a six-axis robot manipulator can be integrated into one field programmable gate array. Finally, to verify the effectiveness and correctness of the proposed field programmable gate array–based servo control integrated chip, a six-axis robot manipulator is applied and some experimental results are demonstrated.

Kinematic Modeling and Hardware Development of 5-DoF Robot Manipulator

This paper presents a 5-DoF articulated robot manipulator and proposes a strategy for solving its inverse kinematics. The Denavit – Hartenberg (D-H) parameterization has been used to model the kinematics of the manipulator. As degree of freedom of manipulator increases, the geometrical solution for inverse kinematics becomes difficult; hence an analytical method for the same is presented. Novelty in the method presented is that no approximations of trigonometric functions are used resulting in a theoretical positional accuracy of 10-10mm of the end-effector. The articulated robotic manipulator developed makes use of integrated actuators and rapid prototyping technology enabling easy replication for educational purposes. The robot arm has been used for manipulation tasks in its workspace successfully.

Adaptive RBF network control for robot manipulators

The uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. This paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. As a novelty, the proposed controller employs a simple Gaussian Radial-Basis-Function network (RBF network) as an uncertainty estimator. The proposed network includes a hidden layer with one node, two inputs and a single output. In comparison with other model-free estimators such as multilayer neural networks and fuzzy systems, the proposed estimator is simpler, less computational and more effective. The weights of the RBF network are tuned online using an adaptation law derived by stability analysis. Despite the majority of previous control approaches which are the torque-based control, the proposed control design is the voltage-based control. Simulations and comparisons with a robust neural network control approach show the efficiency of the proposed control approach applied on the articulated robot manipulator driven by permanent magnet DC motors.

Robots in the shipbuilding industry

In this paper, details of the uses of various robots in the shipbuilding process are provided, with an emphasis on newer developments and applications. The current state of robot applications will be discussed according to the priority of the shipbuilding process. First, various robots for open structures, such as several types of welding carriages and 6-axis articulated robot manipulators , will be reviewed in terms of their mechanisms and applications. Second, several attempts to design autonomous mobile robotic systems for closed blocks of the double-hulled structure of a ship will be discussed in terms of the performance characteristics of their proposed self-traveling mechanisms. Lastly, all corresponding technologies for overcoming structural complexities in closed blocks as well as future directions of robot automation in the shipbuilding industry are also discussed.

A hybrid contact state analysis methodology for robotic-based adjustment of cylindrical pair

The peg-in-hole insertion and adjustment operation is one of the most common tasks in the robotic and automatic assembly processes. Fine motion strategies associated with adjustment operations on a peg-in-hole are fundamental manipulations that can be utilised in dynamic assembly and reconfigurable workholding or fixturing systems. This paper presents a comprehensive study of robotic-based height adjustment of a cylindrical pair based on maintaining minimum contact forces between the links. The outer link is held by the end-effector of a six-DOF (Degrees of freedom) serial articulated robot manipulator. The environment represented by the inner link can be either static or dynamic. A force-based approach and a d value approach are established to determine the type of contact that exists between the links of a cylindrical pair, and to extract control parameters. Based on the comparison and analysis of these two approaches, a hybrid methodology is established by combining a d value approach with a force-based approach for contact state determination. Formulations capable of extracting necessary control parameters, which ensure minimum contact forces between the links, are established from both planar and spatial viewpoints under both static and dynamic environmental conditions. Experimental results demonstrate the effectiveness of the proposed methodology.

Neuro‐adaptive sliding‐mode tracking control of robot manipulators

AbstractIn this work, a new dynamical on‐line learning algorithm for robust model‐free neuro‐adaptive control of a class of nonlinear systems with uncertain dynamics is proposed and experimentally tested in order to evaluate its performance and practical feasibility in industrial settings. The control application studied is the trajectory tracking control task for the first three joints of an open architecture articulated robot manipulator. The control scheme makes use of variable structure systems theory and the feedback‐error‐learning concept. An inner sliding motion is established in terms of the neurocontroller parameters, aiming to lead the error in its control signal towards zero. The outer sliding motion bears on the system under control, the state tracking error vector of which is simultaneously driven towards the origin of the phase space. The existing relation between the two sliding motions is shown. Experimental results illustrate that the proposed neural‐network‐based controller possesses a remarkable learning capability to control complex dynamical systems, virtually without requiring a priori knowledge of the plant dynamics and laborious start‐up procedures. Copyright © 2007 John Wiley & Sons, Ltd.

Highly accurate contour control of an articulated robot manipulator using a Gaussian neural network

PurposeAims to realize the high accurate contour control with high‐speed motion of articulated robot manipulator (ARM) with interference.Design/methodology/approachProposes a new contour control method by using Gaussian neural network (GNN) to solve the problem of the deterioration of the contour control performance due to the interference between robot links. The construction of the GNN controller and the approximation of the interference are based on the Euler‐Lagrange model of ARM. The actual input/out data about the motion of ARM are used for training the GNN to accurately represent the inverse dynamics of ARM with interference. With the Lyapunov function, the stability and the robustness of the GNN controller are discussed. Through the simulation and experiment, it verified that the precision of the contour control has been improved, and illustrated the good features of the proposed method.FindingsFinds that the actual data about the motion of ARM, which is easily obtained from the working field, can express the real features of ARM, and the GNN controller can improve the precision of the contour control with good features.Practical implicationsThe proposed method provides an effective method for realizing high accurate contour control of ARM with interference. It can be extended to the ARMs with more than two links and concerning more factors affecting the precision of the contour control, such as friction or gravity.Originality/valueProposes a new GNN controller for realizing high accurate contour control of ARM with interference, which is significant for industry.

Function-oriented design of a friction stir welding robot

The paper starts with the analysis on the need for intelligent manufacturing systems, and proposes our view of the solution to the problem from a mechatronic point of view. It discusses issues related to the flexible modular systems that produce modular flexible products. The paper takes a novel welding technology called friction stir welding as a case study, and investigates issues related to the design of a machine that could automate the process. It presents a function-oriented approach that could provide the guidelines in development of such a system. Along with the various alternatives of the friction stir welding machines concepts, various types of welding configurations are discussed in detail thereby providing necessary details for function-oriented conceptual design of a general-purpose robotic system. The paper, then, presents the system model for an articulated robot manipulator, as suggested by functional design, followed by simulations to investigate its suitability for such an application. The proposed solution not only ensures the achievement of requirements for the intelligent manufacturing systems, but also provides the necessary guidelines in design and development of such systems, as the concluding remarks. The paper is finalized by future developments and suggestions.

Real-time Velocity Alteration Strategy for Collision-free Trajectory Planning of Two Articulated Robot Manipulators

Two articulated robots working in a shared workspace can be programmed by planning the tip trajectory of each robot independently. To account for collision avoidance between links, a real-time velocity alteration strategy based on fast and accurate collision detection is proposed in this paper to determine the step of next motion of slave (low priority) robot for collision-free trajectory planning of two robots with priorities. The effectiveness of the method depends largely on a newly developed method of accurate estimate of distance between links. By using the enclosing and enclosed ellipsoids representations of polyhedral models of links of robots, the minimum distance estimate and collision detection between the links can be performed more efficiently and accurately. The proposed strategy is implemented in an environment where the geometric paths of robots are pre-planned and the preprogrammed velocities are piecewise constant but adjustable. Under the control of the proposed strategy, the master robot always moves at a constant speed. The slave robot moves at the selected velocity, selected by a tradeoff between collision trend index and velocity reduction in one collision checking time, to keep moving as far as possible and as fast as possible while avoid possible collisions along the path. The collision trend index is a fusion of distance and relative velocity between links of two robots to reflect the possibility of collision at present and in the future. Graphic simulations of two PUMA560 robot arms working in common workspace but with independent goals are conducted. Simulations demonstrate the collision avoidance capability of the proposed approach as compared to the approach based on bounding volumes. It shows that advantage of our approach is less number of speed alterations required to react to potential collisions.

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 Passive Gravity-Compensation System for Articulated Robots

This paper presents a new passive gravity -compensating system for articulated robot manipulators. The system, which consists of linear zero- free -length springs, achieves exact counterbalancing o f the gravitational loads throughout the entire range of the manipulator workspace, A basic concept is to design springs such that the total potential energy of the system including the manipulator and the springs should be maintained constant. A prototype has been developed for a direct-drive five-bar manipulator and its performances have been investigated. Results show that the gravity-induced motor torques have been reduced to less than 5% of those of uncompensated robots. Also, the gravity-compensating system simplifies the position control algorithm while maintaining the trajectory-tracking errors in a satisfactory level. In conclusion, the proposed system efficiently improves the manipulator performances by reducing the driving motor size and the energy consumption as well as by simplifying the control systems.