6-DOF Industrial Robot Research Articles

Virtual realization and geometric discriminant algorithm of the industrial robot end-effector’s position and orientation

Based on geometric characteristics of a typical six DOF industrial robot with the spherical wrist, a discriminant method without solving inverse kinematics equations is proposed for solving the problem whether the robot end-effector can reach the expected position and orientation. Some geometric discrimination conditions are created. Thanks to these geometric discriminant conditions, the visualization of the discriminant result in the virtual environment created in Qt and Ogre3D can be achieved.

Nonlinear Friction and Dynamical Identification for a Robot Manipulator with Improved Cuckoo Search Algorithm

This paper concerns the problem of dynamical identification for an industrial robot manipulator and presents an identification procedure based on an improved cuckoo search algorithm. Firstly, a dynamical model of a 6-DOF industrial serial robot has been derived. And a nonlinear friction model is added to describe the friction characteristic at motion reversal. Secondly, we use a cuckoo search algorithm to identify the unknown parameters. To enhance the performance of the original algorithm, both chaotic operator and emotion operator are employed to help the algorithm jump out of local optimum. Then, the proposed algorithm has been implemented on the first three joints of the ER-16 robot manipulator through an identification experiment. The results show that (1) the proposed algorithm has higher identification accuracy over the cuckoo search algorithm or particle swarm optimization algorithm and (2) compared to linear friction model the nonlinear model can describe the friction characteristic of joints better.

Fuzzy PID based adaptive control on industrial robot system

An importance of Industrial robots have been increasing in many manufacturing firms to maintain quality and productivity. In this paper a fuzzy pid based trajectory tracking of robot manipulator for different structures is proposed which make use for different process with minimum error and these scenario are analyzed using a dynamic robot model. The simulation of fuzzy-pid based control of 6DOF industrial robot shows the better performance of the orientation of the end effectors and joint angular parameters for different structure when compared with the pid controller.

Direct adaptive robust tracking control for 6 DOF industrial robot with enhanced accuracy

A direct adaptive robust tracking control is proposed for trajectory tracking of 6 DOF industrial robot in the presence of parametric uncertainties, external disturbances and uncertain nonlinearities. The controller is designed based on the dynamic characteristics in the working space of the end-effector of the 6 DOF robot. The controller includes robust control term and model compensation term that is developed directly based on the input reference or desired motion trajectory. A projection-type parametric adaptation law is also designed to compensate for parametric estimation errors for the adaptive robust control. The feasibility and effectiveness of the proposed direct adaptive robust control law and the associated projection-type parametric adaptation law have been comparatively evaluated based on two 6 DOF industrial robots. The test results demonstrate that the proposed control can be employed to better maintain the desired trajectory tracking even in the presence of large parametric uncertainties and external disturbances as compared with PD controller and nonlinear controller. The parametric estimates also eventually converge to the real values along with the convergence of tracking errors, which further validate the effectiveness of the proposed parametric adaption law.

New Media Content Platform using 6 –DOF Industrial Robot and 3D Game Engine

New Media Content Platform using 6 –DOF Industrial Robot and 3D Game Engine

English

English

Fault Detection of Gearboxes in an Industrial Robot under Various Operating Conditions

In recent years, industrial robots have been widely used for manufacturing automation. The unexpected failures of the robots could bring about a significant amount of downtime loss due to suspension of the production lines. Fault detection and diagnosis for an industrial robot become one of the backbone technologies in the Industry 4.0. However, the industrial robots operate under variable speeds and loads. This makes fault detection for the industrial robot more challenging. Moreover, signals generated from one arm joint affect those from other joints mutually due to the multiple degree-of-freedom (DOF) motions of the robots. In this paper, we develop a fault detection method for a gearbox, which is one of the most critical components of an industrial robot. Both control and acceleration signals are used for the fault detection. Health data that represent a health state of the robot system are defined as the failure mechanisms of the gears are understood. The effectiveness of the proposed health data is demonstrated using a 6-DOF industrial robot with normal and faulty cases under various operating conditions in terms of rotating speed, rotating directions, number of DOF, different postures of robot arms, and loading condition.

Implicit Robot Force Control Based on Set Invariance

This paper addresses the problem of robot implicit force control by means of set invariance theory. The proposed control law improves the invariance control approach by avoiding the definition of a nominal stabilizing controller, while simultaneously ensuring the absence of output overshoots with respect to the reference. The resulting set invariance based controller is first introduced for a single-input single-output system and then extended to multi-input multi-output systems, in order to be applied to the robot implicit force control problem. Its effectiveness is experimentally validated and compared to state-of-the-art approaches on a hybrid force/position task performed with a 6 DOF industrial robot equipped with a force/torque sensor.

6 DOF Industrial Robot Based on Multi-DOF Counterbalance Mechanism

6 DOF Industrial Robot Based on Multi-DOF Counterbalance Mechanism

FAT-based robust adaptive control of electrically driven robots without velocity measurements

Recently, regressor-free control approach has been presented in which uncertainties are estimated using function approximation techniques (FAT) such as the Fourier series expansion or Legendre polynomials. However, FAT-based observer design remains as an open problem. With this in mind, this paper presents a robust adaptive controller for electrically driven robots, without any need for velocity measurements. The mixed observer/control design procedure is based on universal approximation theory and using Stone–Weierstrass theorem. To highlight the contribution of the paper, it should be emphasized that in comparison with previous related FAT-based controllers, the proposed controller is simpler and less computational. In addition, the number of required Fourier series expansions, control laws, and also adaptation rules has been reduced. Moreover, the observer design is free of model. Simulation results of the controller on a 6-DOF industrial robot manipulator have been presented which proves robustness of the proposed controller against various uncertainties. The results are also compared to those obtained from Chebyshev neural network.

Eye to hand calibration using ANFIS for stereo vision-based object manipulation system

Standard industrial robot manipulator has possibility to manipulate the objects accurately in arbitrary position by using additional vision sensor. This applies in eye-to-hand camera configuration, where the stereo camera can cover the robot arm workspace and the object can be kept accurately for three dimension position estimation. The goal of this system is to control a robot arm to pick up and place the targeted object autonomously within its workspace. In order to accomplish this goal, a stereo vision technique including eye to hand calibration is applied. First, a stereo camera is calibrated to obtain the intrinsic and extrinsic camera parameters. Then, the specific color features of desired object are extracted using image processing algorithms. After that, based on centroid of desired object, 3D (3 dimension) position of the desired object is calculated. Then, camera and robot arm coordinate transformation was calibrated using adaptive artificial network based fuzzy interference system (ANFIS) method. Finally, the 3D coordinates of desired object are sent to robot arm controller as the inputs to move the end-effector equipped with gripper to the object location and pick up the object then place it to the desired location. The experiment was carried out using 6 DOF industrial robot arm and the results demonstrated the good performance of the system with acceptable errors.

Finite Element Analysis and Multibody Dynamics of 6-DOF Industrial Robot

Finite Element Analysis and Multibody Dynamics of 6-DOF Industrial Robot

Orthogonal Image Features for Visual Servoing of a 6-DOF Manipulator With Uncalibrated Stereo Cameras

We present an approach to control a 6-degree-of-freedom (DOF) manipulator using an uncalibrated visual servoing (VS) approach that addresses the challenges of choosing proper image features for target objects and designing a VS controller to enhance the tracking performance. The main contribution of this paper is the definition of a new virtual visual space (image space). A novel stereo camera model employing virtual orthogonal cameras is used to map 6-D poses from Cartesian space to this virtual visual space . Each component of the 6-D pose vector defined in this virtual visual space is linearly independent, leading to a full-rank $6\times 6$ image Jacobian matrix , which allows avoiding classical problems, such as image space singularities and local minima. Furthermore, the control for rotational and translational motion of robot is decoupled due to the diagonal image Jacobian. Finally, simulation results with an eye-to-hand robotic system confirm the improvement in controller stability and motion performance with respect to conventional VS approaches. Experimental results on a 6-DOF industrial robot are provided to illustrate the effectiveness of the proposed method and the feasibility of using this method in practical scenarios.

Development of a 5-DOF arc welding robot

In this paper, a new 5-DOF arc welding robot is introduced by looking at aspects of mechanical design, control system and handheld welding teaching (HWT) method. The structure of this robot is inspired by the functionality of selective compliance assembly robot arms. With the aim to achieve user-oriented HWT, magnet clutches and encoders are adopted into the transmission chains with large reduction ratio. In addition, a gravity balance mechanism is implemented in the robot design to reduce the efforts of operators. The processing of HWT operation is presented with an optimal space arc interpolation algorithm. Two main design characteristics of this robot are low-cost and easy-operation features as compared to conventional 6-DOF industrial robots. Finally, experiments are discussed from laboratory testing the welding performance and results are used to validate the efficiency of the proposed solution.

A fixed-distance planning algorithm for 6-DOF manipulators

Purpose– The purpose of this paper is to propose a new trajectory planning algorithm for industrial robots, which can let the robots move through a desired spatial trajectory, avoid colliding with other objects and achieve accurate movements. Trajectory planning algorithms are the soul of motion control of industrial robots. A predefined space trajectory can let the robot move through the desired spatial coordinates, avoid colliding with other objects and achieve accurate movements.Design/methodology/approach– The mathematical expressions of the proposed algorithm are deduced. The speed control, position control and orientation control strategies are realized and verified with simulations, and then implemented on a six degrees of freedom (6-DOF) industrial robot platform.Findings– A fixed-distance trajectory planning algorithm based on Cartesian coordinates was presented. The linear trajectory, circular trajectory, helical trajectory and parabolic trajectory in Cartesian coordinates were implemented on the 6-DOF industrial robot.Originality/value– A simple and efficient algorithm is proposed. Enrich the kind of trajectory which the industrial robot can realize. In addition, the industrial robot can move more concisely, smoothly and precisely.

Implementation of Robot Control Algorithms by Real-Time Control System

The paper deals with development and implementation of the direct and inverse kinematics to control of 6 DOF industrial robot SEF-ROBOTER SR25 by a real time control system. To obtain the angular position of each joint an iterative algorithm is applied that is developed in the Simulink program. This solution creates a basis for real time control of the robot drives utilizing features of SIEMENS SINAMICS family of frequency converters. The developed control system presents a universal platform enabling to debug any robot control algorithm and also easy to change a desired trajectory of the end effector. The equipment is suitable for testing different trajectories of the robot and is suitable also for educational purposes.

Toward Welding Robot With Human Knowledge: A Remotely-Controlled Approach

This paper presents a remotely controlled welding scheme that enables transformation of human welder knowledge into a welding robot. In particular, a 6-DOF UR-5 industrial robot arm is equipped with sensors to observe the welding process, including a compact 3D weld pool surface sensing system and an additional camera to provide direct view of the work-piece. Human welder operates a virtual welding torch, whose motion is tracked by a Leap sensor. To remotely operate the robot based on the motion information from the Leap sensor, a predictive control approach is proposed to accurately track the human motion by controlling the speed of the robot arm movement. Tracking experiments are conducted to track both simulated movement with varying speed and actual human hand movement. It is found that the proposed predictive controller is able to track human hand movement with satisfactory accuracy. A welding experiment has also been conducted to verify the effectiveness of the proposed remotely-controlled welding system. A foundation is thus established to realize teleoperation and help transfer human knowledge to the welding robot.

Dynamic Model Identification for 6-DOF Industrial Robots

A complete and systematic procedure for the dynamical parameters identification of industrial robot manipulator is presented. The system model of robot including joint friction model is linear with respect to the dynamical parameters. Identification experiments are carried out for a 6-degree-of-freedom (DOF) ER-16 robot. Relevant data is sampled while the robot is tracking optimal trajectories that excite the system. The artificial bee colony algorithm is introduced to estimate the unknown parameters. And we validate the dynamical model according to torque prediction accuracy. All the results are presented to demonstrate the efficiency of our proposed identification algorithm and the accuracy of the identified robot model.

Design and Experimental Testing of a Robotic System for High Speed Recording

The high-speed filming industry sets tasks demanding complex camera movement, such as shooting along a nonlinear trajectory relative to a freely falling body. Such sophisticated requirements can be completed only by means of a mechatronic or robotic system. To solve these problems we have created a robotic system consisting of a 6-DOF industrial robot with a high-speed camera fixed on the flange. In order to ensure precise timing and repeatability of the shooting we have developed a synchronization device and a number of custom automatic dispensers. The prototype was tested with a high-speed camera on a number of real-world tasks with different types of movement.

Direct Joint Space State Estimation in Robots With Multiple Elastic Joints

For robots with joint elasticity, discrepancies exist between the motor side and the load side (e.g., the link of the robotic joint). Thus, the load side (end-effector) performance can hardly be guaranteed with motor side measurements alone. In this paper, a computationally efficient load side state estimation scheme is proposed for the multi-joint robot with joint elasticity, which is equipped with motor encoders and a low-cost end-effector MEMS sensor such as a three-axial accelerometer. An optimization-based inverse differential kinematics algorithm is developed to obtain the load side joint state rough estimates. With these rough estimates, the estimation problem is decoupled into simple second-order kinematic Kalman filter for each joint to refine the joint position and velocity estimates. Maximum likelihood principle is utilized to estimate the fictitious noise covariances used in the Kalman filter. Both offline and online solutions are derived. The extensions to other sensor configurations are discussed as well. The effectiveness of the developed method is validated through the simulation and the experimental study on a 6-DOF industrial robot.