scholarly journals A postprocessing and path optimization based on nonlinear error for multijoint industrial robot-based 3D printing

2020 ◽  
Vol 17 (5) ◽  
pp. 172988142095224
Author(s):  
Guoqiang Fu ◽  
Tengda Gu ◽  
Hongli Gao ◽  
Caijiang Lu
Keyword(s):  
3D Printing ◽  
Joint Angle ◽  
Industrial Robot ◽  
Optimization Method ◽  
Industrial Robots ◽  
Numerical Control ◽  
Path Optimization ◽  
Nc Code ◽  
Nonlinear Error ◽  
Rotational Joint

Multijoint industrial robots can be used for 3D printing to manufacture the complex freeform surfaces. The postprocessing is the basis of the precise printing. Due to the nonlinear motion of the rotational joint, nonlinear error is inevitable in multijoint industrial robots. In this article, the postprocessing and the path optimization based on the nonlinear errors are proposed to improve the accuracy of the multijoint industrial robots-based 3D printing. Firstly, the kinematics of the multijoint industrial robot for 3D printing is analyzed briefly based on product of exponential (POE) theory by considering the structure parameters. All possible groups of joint angles for one tool pose in the joint range are obtained in the inverse kinematics. Secondly, the nonlinear error evaluation based on the interpolation is derived according to the kinematics. The nonlinear error of one numerical control (NC) code or one tool pose is obtained. The principle of minimum nonlinear error of joint angle is proposed to select the appropriate solution of joint angle for the postprocessing. Thirdly, a path smoothing method by inserting new tool poses adaptively is proposed to reduce the nonlinear error of the whole printing path. The smooth level in the smoothing is proposed to avoid the endless insertion near the singular area. Finally, simulation and experiments are carried out to testify the effectiveness of the proposed postprocessing and path optimization method.

Cable-path optimization method for industrial robot arms

2022 ◽  
Vol 73 ◽  
pp. 102245
Author(s):  
Shintaro Iwamura ◽  
Yoshiki Mizukami ◽  
Takahiro Endo ◽  
Fumitoshi Matsuno
Keyword(s):  
Industrial Robot ◽  
Optimization Method ◽  
Path Optimization ◽  
Robot Arms

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 Workspace Visualization Method for a Multijoint Industrial Robot Based on the 3D-Printing Layering Concept

2020 ◽  
Vol 10 (15) ◽  
pp. 5241
Author(s):  
Guoqiang Fu ◽  
Chun Tao ◽  
Tengda Gu ◽  
Caijiang Lu ◽  
Hongli Gao ◽  
...  
Keyword(s):  
3D Printing ◽  
Joint Angle ◽  
Industrial Robot ◽  
Selection Method ◽  
Forward Kinematics ◽  
Visualization Method ◽  
Joint Angles ◽  
Boundary Extraction ◽  
Simulation And Experiment ◽  
Constraint Information

The workspace of a robot provides the necessary constraint information for path planning and reliable control of the robot. In this paper, a workspace visualization method for a multijoint industrial robot is proposed to obtain a detailed workspace by introducing the 3D-printing layering concept. Firstly, all possible joint-angle groups of one pose in the joints’ ranges are calculated in detail according to the POE (product of exponential) theory-based forward-kinematics expressions of the multijoint industrial robot. Secondly, a multisolution selection method based on the key degree of the joint is proposed to select the appropriate joint-angle groups. The key degrees of all joints and their key order are obtained according to the sensitivity expressions of all joint angles, calculated from the Jacobian matrix of the robot. One principle based on the smallest differences of the nominal angle is established to select the possible solutions for one joint from the possible solutions for the joint with the smaller key order. The possible solutions for the joint with the highest key order are the appropriate joint-angle group. Thirdly, a workspace visualization method based on the layering concept of 3D printing is presented to obtain a detailed workspace for a multijoint industrial robot. The boundary formula of each layer is derived by forward kinematics, which is expressed as a circle or a ring. The maximum and minimum values of the radius are obtained according to the travel range of the joint angles. The height limitations of all layers are obtained with forward kinematics. A workspace boundary-extraction method is presented to obtain the array of path points of the boundary at each layer. The proposed postprocessing method is used to generate the joint-angle code of each layer for direct 3D printing. Finally, the effectiveness of the multisolution selection method and the workspace visualization method were verified by simulation and experiment.

Robotic CAM System Available for Both CL Data and NC Data

2013 ◽  
pp. 265-276 ◽  
Author(s):  
Fusaomi Nagata ◽  
Sho Yoshitake ◽  
Keigo Watanabe ◽  
Maki K. Habib
Keyword(s):  
Industrial Robot ◽  
Industrial Robots ◽  
Numerical Control ◽  
Open Architecture ◽  
Experimental Result ◽  
Location Data ◽  
Cad Cam ◽  
Nc Machine ◽  
Servo Controller ◽  
Nc Data

This chapter describes the development of a robotic CAM system for an articulated industrial robot from the viewpoint of robotic servo controller. It is defined here that the CAM system includes an important function that allows an industrial robot to move along not only numerical control data (NC data) but also cutter location data (CL data) consisting of position and orientation components. A reverse post-processor is proposed for the robotic CAM system to online generate CL data from the NC data generated for a five-axis NC machine tool with a tilting head, and the transformation accuracy about orientation components in CL data is briefly evaluated. The developed CAM system has a high applicability to other industrial robots with an open architecture controller whose servo system is technically opened to end-users, and also works as a straightforward interface between a general CAD/CAM system and an industrial robot. The basic design of the robotic CAM system and the experimental result are presented, in which an industrial robot can move based on not only CL data but also NC data without any teaching.

scholarly journals Predicting Positioning Error and Finding Features for Large Industrial Robots Based on Deep Learning

2021 ◽  
Vol 15 (2) ◽  
pp. 206-214
Author(s):  
Daiki Kato ◽  
Kenya Yoshitsugu ◽  
Toshiki Hirogaki ◽  
Eiichi Aoyama ◽  
Kenichi Takahashi ◽  
...  
Keyword(s):  
Deep Learning ◽  
Computer Aided Design ◽  
Joint Angle ◽  
Industrial Robot ◽  
Movement Time ◽  
Vertical Axis ◽  
Industrial Robots ◽  
Positioning Error ◽  
Design Data ◽  
End Effector

In this study, we evaluated the motion accuracy of a large industrial robot and its compensation method and constructed an off-line teaching operation based on three-dimensional computer aided design data. In this experiment, we used a laser tracker to measure the coordinates of the end effector of the robot. Simultaneously, the end-effector coordinates, each joint angle, the maximum current of the motors attached to each joint, and rotation speed of each joint were measured. This servo information was converted into image data as visible information. For each robot movement path, an image was created; the horizontal axis represented the movement time of the robot and the vertical axis represented the servo information. A convolutional neural network (CNN), a type of deep learning, was used to predict the positioning error with high accuracy. Subsequently, to identify the features of the positioning error, the image was divided into several analysis areas, one of which was filled with various colors and analyzed by the CNN. If the prediction accuracy of the CNN decreased, then the analysis area would be identified as a feature. Thus, the features of the Y-axis positioning error were observed for teaching each joint angle in the opposite direction just after the start of the motion, overshoot of the rotational joint current, and the change in the swivel joint current.

Robotic CAM System Available for Both CL Data and NC Data

2019 ◽  
pp. 663-679
Author(s):  
Fusaomi Nagata ◽  
Sho Yoshitake ◽  
Keigo Watanabe ◽  
Maki K. Habib
Keyword(s):  
Industrial Robot ◽  
Industrial Robots ◽  
Numerical Control ◽  
Open Architecture ◽  
Experimental Result ◽  
Location Data ◽  
Cad Cam ◽  
Nc Machine ◽  
Servo Controller ◽  
Nc Data

This chapter describes the development of a robotic CAM system for an articulated industrial robot from the viewpoint of robotic servo controller. It is defined here that the CAM system includes an important function that allows an industrial robot to move along not only numerical control data (NC data) but also cutter location data (CL data) consisting of position and orientation components. A reverse post-processor is proposed for the robotic CAM system to online generate CL data from the NC data generated for a five-axis NC machine tool with a tilting head, and the transformation accuracy about orientation components in CL data is briefly evaluated. The developed CAM system has a high applicability to other industrial robots with an open architecture controller whose servo system is technically opened to end-users, and also works as a straightforward interface between a general CAD/CAM system and an industrial robot. The basic design of the robotic CAM system and the experimental result are presented, in which an industrial robot can move based on not only CL data but also NC data without any teaching.

Optimization Trajectory in Handling with the Same Object

2014 ◽  
Vol 613 ◽  
pp. 230-235
Author(s):  
Marek Vagaš
Keyword(s):  
Trajectory Optimization ◽  
Industrial Robot ◽  
Optimization Method ◽  
Industrial Robots ◽  
Optimization Strategy ◽  
Mechanical Resonance ◽  
Resonance Modes ◽  
Robot Trajectory ◽  
Point To Point ◽  
Point Type

In this paper, there is presented an industrial robot trajectory optimization method for series of point-to-point type movements. Also contain an optimization strategy that has been built using through proposed automated optimizing system for handling. The optimized trajectories must lead to avoid exciting mechanical resonance modes of the industrial robot structure. This can be achieved by applying of robot interpolation. The testing results show that the trajectory optimization through this method is feasible for industrial robots.

Development of Robotic CAM System That Generates Online Motion Supported by CLS and NC Data

2020 ◽  
pp. 1-27
Author(s):  
Fusaomi Nagata ◽  
Maki K. Habib ◽  
Takamasa Kusano ◽  
Keigo Watanabe
Keyword(s):  
Motion Control ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Numerical Control ◽  
Open Architecture ◽  
Time Motion ◽  
Cad Cam ◽  
Position And Orientation ◽  
Nc Data ◽  
Cam Systems

This chapter describes the development of a robotic CAM system for six-DOFs articulated industrial robot to generate online motion supported by cutter location source (CLS) data and numerical control (NC) data. The robotic CAM system realizes a practical data interface between industrial robots with open architecture controllers and commercially available CAD/CAM systems, and it includes functions that generate minute position and orientation components for real time motion control from CLS data and NC data without the need for teaching. The design principles of the developed robotic CAM system, and the experimental results on three real robots, RV1A, VS068, and FANUC R2000iC, are presented and demonstrated using both CLS and NC data generated through the developed CAM system.

scholarly journals Human-Machine Cooperation and Path Planning for Complex Road Conditions

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Guanghong Zhou
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Industrial Robot ◽  
Rapid Development ◽  
Industrial Robots ◽  
Path Optimization ◽  
Planning System ◽  
Target Point ◽  
Planning Algorithm ◽  
Path Planning Algorithm

With the rapid development of the information age, the development of industrial robots is also advancing by leaps and bounds. In the scenes of automobile, medicine, aerospace, and public service, we have fully enjoyed the convenience brought by industrial robots. However, with the continuous development of industrial robot-related concepts and technologies, human-computer interaction and cooperation have become the development trend of industrial robot. In this paper, the human-machine cooperation and path optimization of industrial robot in a complex road environment are studied and analyzed. At the theoretical modeling level, firstly, the industrial robot is modeled and obstacle avoidance is analyzed based on the kinematics of industrial robot; thus, an efficient and concise collision detection model of industrial robot is proposed. At the algorithm level, in view of the complex road conditions faced by industrial robots, this paper will study and analyze the obstacle avoidance strategy of human-computer cooperation and real-time path optimization algorithm of industrial robots. Based on the virtual target point algorithm, this paper further improves the problem that the goal of the traditional path planning algorithm cannot be fully covered, so as to propose the corresponding improved path planning algorithm of industrial robots. In the experimental part, based on the existing industrial robot system, the human-machine cooperation and path planning system proposed in this paper are designed. The experimental results show that the algorithm proposed in this paper improves the accuracy of obstacle avoidance by about 10 points and the corresponding convergence speed by about 5% compared with the traditional algorithm and the experimental effect is remarkable.

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