scholarly journals Dynamic Hybrid Filter for Vision-Based Pose Estimation of a Hexa Parallel Robot

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Ba-Phuc Huynh ◽  
Yong-Lin Kuo
Keyword(s):  
Pose Estimation ◽  
Unscented Kalman Filter ◽  
Vision System ◽  
Parallel Robot ◽  
Industrial Robots ◽  
Feature Points ◽  
Hybrid Filter ◽  
Color Feature ◽  
End Effector ◽  
Dynamic Hybrid

One of the problems with industrial robots is their ability to accurately locate the pose of the end-effector. Over the years, many other solutions have been studied including static calibration and dynamic positioning. This paper presents a novel approach for pose estimation of a Hexa parallel robot. The vision system uses three simple color feature points fixed on the surface of the end-effector to measure the pose of the robot. The Intel RealSense Camera D435i is used as a 3D measurement of feature points, which offers a cheap solution and high accuracy in positioning. Based on the constraint of three color feature points, the pose of the end-effector, including position and orientation, is determined. A dynamic hybrid filter is designed to correct the vision-based pose measurement. The complementary filter is used to eliminate the noise of image processing due to environmental light source interference. The unscented Kalman filter is designed to smooth out the pose estimation of the vision system based on robot’s kinematic parameters. The combination of two filters in the same control scheme contributes to increased stability and improved accuracy of robot’s positioning. The simulation, experiment, and comparison demonstrate the effectiveness and feasibility of the proposed method.

scholarly journals End-Effector Pose Estimation in Complex Environments Using Complementary Enhancement and Adaptive Fusion of Multisensor

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Mingrui Luo ◽  
En Li ◽  
Rui Guo ◽  
Jiaxin Liu ◽  
Zize Liang
Keyword(s):  
Kalman Filter ◽  
Pose Estimation ◽  
Unscented Kalman Filter ◽  
Rbf Neural Network ◽  
Estimation Error ◽  
Estimation Method ◽  
Original Data ◽  
Measurement Unit ◽  
Complex Environments ◽  
End Effector

Redundant manipulators are suitable for working in narrow and complex environments due to their flexibility. However, a large number of joints and long slender links make it hard to obtain the accurate end-effector pose of the redundant manipulator directly through the encoders. In this paper, a pose estimation method is proposed with the fusion of vision sensors, inertial sensors, and encoders. Firstly, according to the complementary characteristics of each measurement unit in the sensors, the original data is corrected and enhanced. Furthermore, an improved Kalman filter (KF) algorithm is adopted for data fusion by establishing the nonlinear motion prediction of the end-effector and the synchronization update model of the multirate sensors. Finally, the radial basis function (RBF) neural network is used to adaptively adjust the fusion parameters. It is verified in experiments that the proposed method achieves better performances on estimation error and update frequency than the original extended Kalman filter (EKF) and unscented Kalman filter (UKF) algorithm, especially in complex environments.

scholarly journals RGB-D-Based Pose Estimation of Workpieces with Semantic Segmentation and Point Cloud Registration

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1873 ◽  
Author(s):  
Hui Xu ◽  
Guodong Chen ◽  
Zhenhua Wang ◽  
Lining Sun ◽  
Fan Su
Keyword(s):  
Pose Estimation ◽  
Point Cloud ◽  
Evaluation Method ◽  
Vision System ◽  
Robot Vision ◽  
Semantic Segmentation ◽  
Industrial Robots ◽  
Depth Information ◽  
Point Cloud Registration ◽  
Convolutional Network

As an important part of a factory’s automated production line, industrial robots can perform a variety of tasks by integrating external sensors. Among these tasks, grasping scattered workpieces on the industrial assembly line has always been a prominent and difficult point in robot manipulation research. By using RGB-D (color and depth) information, we propose an efficient and practical solution that fuses the approaches of semantic segmentation and point cloud registration to perform object recognition and pose estimation. Different from objects in an indoor environment, the characteristics of the workpiece are relatively simple; thus, we create and label an RGB image dataset from a variety of industrial scenarios and train the modified FCN (Fully Convolutional Network) on a homemade dataset to infer the semantic segmentation results of the input images. Then, we determine the point cloud of the workpieces by incorporating the depth information to estimate the real-time pose of the workpieces. To evaluate the accuracy of the solution, we propose a novel pose error evaluation method based on the robot vision system. This method does not rely on expensive measuring equipment and can also obtain accurate evaluation results. In an industrial scenario, our solution has a rotation error less than two degrees and a translation error < 10 mm.

scholarly journals Vision/Position Hybrid Control for a Hexa Robot Using Bacterial Foraging Optimization in Real-time Pose Adjustment

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 564
Author(s):  
Ba-Phuc Huynh ◽  
Shun-Feng Su ◽  
Yong-Lin Kuo
Keyword(s):  
Real Time ◽  
Optimization Problem ◽  
Closed Loop ◽  
Hybrid Control ◽  
Vision System ◽  
Parallel Robot ◽  
Bacterial Foraging Optimization ◽  
3D Vision ◽  
End Effector ◽  
Bacterial Foraging

This paper presents a novel architecture of the vision/position hybrid control for a Hexa parallel robot. The 3D vision system is combined with the Proportional-Integral-Derivative (PID) position controller to form a two-level closed-loop controller of the robot. The 3D vision system measures the pose of the end-effector after the PID control. The measurement of the 3D vision system is used as a feedback of the second closed-loop control. The 3D vision system has a simple structure using two fixed symmetric cameras at the top of the robot and four planar colored markers on the surface of the end-effector. The 3D vision system detects and reconstructs the 3D coordinates of colored markers. Based on the distance and coplanarity constraints of the colored markers, the optimization problem is modeled for the real-time adjustment, which is implemented during the operation of the robot to minimize the measurement error of the 3D vision system due to both the initial calibration of the stereo camera and the external noise affecting image processing. The bacterial foraging optimization is appropriately configured to solve the optimization problem. The experiment is performed on a specific Hexa parallel robot to assess the effectiveness and feasibility of the proposed real-time adjustment using the bacterial foraging optimization. The experimental result shows that it has high accuracy and fast computation time although the experiment is conducted on a laptop with an average hardware configuration. An experimental comparison of the performance between the proposed method and another control method is also implemented. The results show the superiority and application potential of the proposed method.

Kinematic analysis and design of a novel 6-degree of freedom parallel robot

2014 ◽  
Vol 229 (2) ◽  
pp. 291-303 ◽  
Author(s):  
DU Hui ◽  
GAO Feng ◽  
PAN Yang
Keyword(s):  
Set Theory ◽  
Kinematic Analysis ◽  
Parallel Mechanism ◽  
Design Methodology ◽  
Parallel Robot ◽  
End Effector ◽  
Analysis And Design ◽  
Velocity Models ◽  
Reachable Workspace ◽  
Rotational Motions

A novel 3-UP3R parallel mechanism with six degree of freedoms is proposed in this paper. One most important advantage of this mechanism is that the three translational and three rotational motions are partially decoupled: the end-effector position is only determined by three inputs, while the rotational angles are relative to all six inputs. The design methodology via GF set theory is brought out, using which the limb type can be determined. The mobility of the end-effector is analyzed. After that, the kinematic and velocity models are formulated. Then, workspace is studied, and since the robot is partially decoupled, the reachable workspace is also the dexterous workspace. In the end, both local and global performances are discussed using conditioning indexes. The experiment of real prototype shows that this mechanism works well and may be applied in many fields.

Three-Degree-of-Freedom Parallel Robot Arm

2006 ◽  
Author(s):  
Martin Hosek ◽  
Michael Valasek ◽  
Jairo Moura
Keyword(s):  
Parallel Robot ◽  
Degree Of Freedom ◽  
Motion Path ◽  
Angular Orientation ◽  
Robot Arm ◽  
Flat Panel Display ◽  
End Effector ◽  
Cluster Tools ◽  
Manufacturing Applications ◽  
Three Degree Of Freedom

This paper presents single- and dual-end-effector configurations of a planar three-degree of freedom parallel robot arm designed for automated pick-place operations in vacuum cluster tools for semiconductor and flat-panel-display manufacturing applications. The basic single end-effector configuration of the arm consists of a pivoting base platform, two elbow platforms and a wrist platform, which are connected through two symmetric pairs of parallelogram mechanisms. The wrist platform carries an end-effector, the position and angular orientation of which can be controlled independently by three motors located at the base of the robot. The joints and links of the mechanism are arranged in a unique geometric configuration which provides a sufficient range of motion for typical vacuum cluster tools. The geometric properties of the mechanism are further optimized for a given motion path of the robot. In addition to the basic symmetric single end-effector configuration, an asymmetric costeffective version of the mechanism is derived, and two dual-end-effector alternatives for improved throughput performance are described. In contrast to prior attempts to control angular orientation of the end-effector(s) of the conventional arms employed currently in vacuum cluster tools, all of the motors that drive the arm can be located at the stationary base of the robot with no need for joint actuators carried by the arm or complicated belt arrangements running through the arm. As a result, the motors do not contribute to the mass and inertia properties of the moving parts of the arm, no power and signal wires through the arm are necessary, the reliability and maintenance aspects of operation are improved, and the level of undesirable particle generation is reduced. This is particularly beneficial for high-throughput applications in vacuum and particlesensitive environments.

scholarly journals Proposal of a Decoupled Structure of Fuzzy-PID Controllers Applied to the Position Control in a Planar CDPR

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 745
Author(s):  
Marco Carpio ◽  
Roque Saltaren ◽  
Julio Viola ◽  
Cristian Calderon ◽  
Juan Guerra
Keyword(s):  
Position Control ◽  
Control Structure ◽  
Parallel Robot ◽  
Pid Controllers ◽  
Fuzzy Pid ◽  
End Effector ◽  
Robot Systems ◽  
Decoupled Control ◽  
The Mathematical Model ◽  
Decoupled Structure

The design of robot systems controlled by cables can be relatively difficult when it is approached from the mathematical model of the mechanism, considering that its approach involves non-linearities associated with different components, such as cables and pulleys. In this work, a simple and practical decoupled control structure proposal that requires practically no mathematical analysis was developed for the position control of a planar cable-driven parallel robot (CDPR). This structure was implemented using non-linear fuzzy PID and classic PID controllers, allowing performance comparisons to be established. For the development of this research, first the structure of the control system was proposed, based on an analysis of the cables involved in the movement of the end-effector (EE) of the robot when they act independently for each axis. Then a tuning of rules was carried out for fuzzy PID controllers, and Ziegler–Nichols tuning was applied to classic PID controllers. Finally, simulations were performed in MATLAB with the Simulink and Simscape tools. The results obtained allowed us to observe the effectiveness of the proposed structure, with noticeably better performance obtained from the fuzzy PID controllers.

Finding Features of Positioning Error for Large Industrial Robots Based on Convolutional Neural Network

2021 ◽  
Author(s):  
Daiki Kato ◽  
Kenya Yoshitugu ◽  
Naoki Maeda ◽  
Toshiki Hirogaki ◽  
Eiichi Aoyama ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Production Systems ◽  
Industrial Robot ◽  
Three Dimensional ◽  
Industrial Robots ◽  
Numerical Control ◽  
Robot Motion ◽  
Positioning Error ◽  
End Effector

Abstract Most industrial robots are taught using the teaching playback method; therefore, they are unsuitable for use in variable production systems. Although offline teaching methods have been developed, they have not been practiced because of the low accuracy of the position and posture of the end-effector. Therefore, many studies have attempted to calibrate the position and posture but have not reached a practical level, as such methods consider the joint angle when the robot is stationary rather than the features during robot motion. Currently, it is easy to obtain servo information under numerical control operations owing to the Internet of Things technologies. In this study, we propose a method for obtaining servo information during robot motion and converting it into images to find features using a convolutional neural network (CNN). Herein, a large industrial robot was used. The three-dimensional coordinates of the end-effector were obtained using a laser tracker. The positioning error of the robot was accurately learned by the CNN. We extracted the features of the points where the positioning error was extremely large. By extracting the features of the X-axis positioning error using the CNN, the joint 1 current is a feature. This indicates that the vibration current in joint 1 is a factor in the X-axis positioning error.

scholarly journals A Novel Kinematically Redundant Planar Parallel Robot Manipulator With Full Rotatability

2018 ◽  
Vol 11 (1) ◽  
Author(s):  
Nicholas Baron ◽  
Andrew Philippides ◽  
Nicolas Rojas
Keyword(s):  
Potential Application ◽  
Robot Manipulator ◽  
Video Recording ◽  
Parallel Robot ◽  
Singularity Analysis ◽  
Geometric Method ◽  
Forward Kinematics ◽  
Online Video ◽  
End Effector ◽  
Moving Platform

This paper presents a novel kinematically redundant planar parallel robot manipulator, which has full rotatability. The proposed robot manipulator has an architecture that corresponds to a fundamental truss, meaning that it does not contain internal rigid structures when the actuators are locked. This also implies that its rigidity is not inherited from more general architectures or resulting from the combination of other fundamental structures. The introduced topology is a departure from the standard 3-RPR (or 3-RRR) mechanism on which most kinematically redundant planar parallel robot manipulators are based. The robot manipulator consists of a moving platform that is connected to the base via two RRR legs and connected to a ternary link, which is joined to the base by a passive revolute joint, via two other RRR legs. The resulting robot mechanism is kinematically redundant, being able to avoid the production of singularities and having unlimited rotational capability. The inverse and forward kinematics analyses of this novel robot manipulator are derived using distance-based techniques, and the singularity analysis is performed using a geometric method based on the properties of instantaneous centers of rotation. An example robot mechanism is analyzed numerically and physically tested; and a test trajectory where the end effector completes a full cycle rotation is reported. A link to an online video recording of such a capability, along with the avoidance of singularities and a potential application, is also provided.

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