scholarly journals Cartesian space robot manipulator clamping movement in ROS simulation and experiment

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Longtao Mu ◽  
Yunfei Zhou ◽  
Tiebiao Zhao
Keyword(s):  
Motion Planning ◽  
Position Control ◽  
Robot Manipulator ◽  
Robotic Arm ◽  
Robot Motion ◽  
Robot Arm ◽  
Operation System ◽  
Model File ◽  
Simulation And Experiment ◽  
Tool Centre Point

Abstract This paper studies the robot arm sorting position control based on robot operation system (ROS), which works depending on the characteristics of the robot arm sorting operation using the top method, to automate the sorting operation and improve the work efficiency of workpiece sorting. Through the ROS MoveIt! module, the sorting pose and movement path of the robotic arm are planned, the inverse kinematics of the sorting robotic arm is solved, and the movement pose characteristics of the sorting robotic arm are analysed. The robot arm model was created using Solidworks software, and the URDF model file of the robot arm was exported through the sw2urdf plugin conversion tool, and the parameters were configured. Based on ROS for 6-degree-of-freedom (DOF) robot motion simulation, random extended tree (RRT) algorithm from open motion planning library (OMPL) is selected. The robot motion planning analysis and sorting manipulator drive UR5 manipulator. The results show that the sorting pose and motion trajectory of the robot arm are determined by controlling the sorting pose of the sorting robot arm, and the maximum radius value of the tool centre point (TCP) rotation of the robot arm and the position of the workpiece are obtained. This method can improve the success rate of industrial sorting robots in grabbing objects. This analysis is of great significance to the research of robots’ autonomous object grabbing.

scholarly journals Modeling Method of Autonomous Robot Manipulator Based on D-H Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jie Cai ◽  
Jinlian Deng ◽  
Wei Zhang ◽  
Weisheng Zhao
Keyword(s):  
Robot Manipulator ◽  
Algebraic Method ◽  
Modeling Method ◽  
Inverse Solution ◽  
Geometric Method ◽  
Experimental Simulation ◽  
Robotic Arm ◽  
Robot Arm ◽  
Robotic Arms ◽  
Joint Variable

With the continuous development of science and technology, robotics is widely used in various fields. In recent years, more and more research studies have been done on the control of autonomous robotic manipulators. How to quickly, accurately, and smoothly grasp objects has always been a difficult point of research. As the robot’s executive mechanism, the robot arm plays an important role in whether the robot can complete a specific task. Therefore, the research on the robot arm is also the main topic in the development of robot technology. The control theory, kinematics, and human-computer interaction of robotic arms are the focus of the research in the field of robotic arms. Based on the above background, the research content of this paper is the research on the modeling method of autonomous robotic manipulator based on D-H algorithm. This paper uses D-H modeling method to model a four-degree-of-freedom robotic arm and gives the forward kinematics equation of the robotic arm. The inverse solution of the manipulator was given by the method and the geometric method, and the joint variable values were calculated. Finally, through experimental simulation, the experimental results show that the inverse solution of the end position of the machine by the geometric method is in the range of 2∼4 mm, and the inverse solution of the end position of the machine by the algebraic method is in the range of 6∼14 mm. It is more accurate to find the inverse solution of the geometrical method of the manipulator than the algebraic method.

Computer simulation of sensor-based robot collision avoidance in an unknown environment

Robotica ◽  
1987 ◽  
Vol 5 (4) ◽  
pp. 291-302 ◽  
Author(s):  
K. Sun ◽  
V. Lumelsky
Keyword(s):  
Computer Simulation ◽  
Motion Planning ◽  
Collision Avoidance ◽  
Autonomous Vehicle ◽  
Planning System ◽  
Robot Motion ◽  
Robot Arm ◽  
Fixed Base ◽  
The One ◽  
Robot Path

SUMMARYComputer simulation is a major tool in validation of robot motion planning systems, since, on the one hand, underlying theory of algorithms typically requires questionable assumptions and simplifications, and, on the other hand, experiments with hardware are necessarily limited by available resources and time. This is especially true when the motion planning system in question is based on sensor feedback and the generated trajectory is, therefore, unpredictable. This paper describes a simulation system ROPAS (for RObot PAth Simulation) for testing one approach — called Dynmic Path Planning (DPP) — to sensor-based robot collision avoidance in an environment with unknown obstacles. Using real time graphics animation of the motion planning system, the user can simulate the behavior of an autonomous vehicle or a robot arm manipulator with a fixed base. The overall structure of the system is described, and examples are presented.

scholarly journals Design and Fabrication of 3-DOF Robot Arm Using Parallelogram Mechanisms

2021 ◽  
Vol 9 (9) ◽  
pp. 1224-1229
Keyword(s):  
Robotic Arm ◽  
Robot Motion ◽  
3D Printer ◽  
File Format ◽  
Robot Arm ◽  
End Effector ◽  
Stl File ◽  
Stepper Motors ◽  
And Control

This paper focuses on the design, fabrication and control of a 3-DOF robot arm using stepper motors. The robot arm uses three parallelogram mechanisms to position the end-effector of the robot and keep the end-effector always parallel to the horizontal during the robot motion. The robot is designed on the Autodesk Inventor software. Separated parts of the robot are saved in the stereolithography (STL) file format. Then the parts are fabricated by a 3D printer. The movement of the robotic arm is driven by stepper motors and controlled by Arduino. The Arduino board implements kinematics calculation, creates pulses and sends them to three drivers to driven stepper motors. A software is developed to control the robot by sending the command to the Arduino board.

scholarly journals CONTROL SYSTEM OF ROBOT MANIPULATOR BASED ON DIGITAL CONTROLLER

2021 ◽  
pp. 257-263
Author(s):  
Ivan Biliuk ◽  
Serhii Havrylov ◽  
Oleh Savchenko ◽  
Dmitro Shareyko ◽  
Oleksandr Maiboroda ◽  
...  
Keyword(s):  
Control System ◽  
Motion Control ◽  
Position Control ◽  
Robot Manipulator ◽  
Digital Controller ◽  
Robotic Arm ◽  
Control Approach ◽  
Dc Motors ◽  
Position Regulation ◽  
Permanent Magnet Dc Motors

In the last years, many researches have proposed concerning the motion control and position regulation for manipulators. Motion control has important applications in many areas, for example industrial robotics. In this paper control system based on digital controller for the position control of robotic arm manipulator are build. The proposed control system was simulated on a robot manipulator driven by permanent magnet dc motors. Simulation results show the effectiveness of the control approach.

scholarly journals Implementasi Persamaan Kinematik Maju Pada Robot Manipulator

2014 ◽  
Vol 6 (1) ◽  
pp. 66-75
Author(s):  
Herizon Herizon ◽  
Ade Diana
Keyword(s):  
Degrees Of Freedom ◽  
Robot Manipulator ◽  
Angular Position ◽  
Robotic Arm ◽  
Equation Modeling ◽  
Forward Kinematics ◽  
Robot Arm ◽  
Kinematics Modeling ◽  
Trigonometric Equations ◽  
Manipulator Control

Robot is one technology that is being developed at this time. Robot manipulators are widely used in industry, especially robotic arm that has a certain degree of freedom. The problems that occurred in the robot arm is the accuracy in determining the position of the object to be moved. This study aims to apply the method forward kinematics equation modeling on the movement of the robot manipulator in particular robot arm 3 degrees of freedom (DOF) equipped with a gripper which serves to clamp and move the object. The method used in this study is an experimental method in phases: the design of hardware and software, interconnect hardware and software in the system of movement of the robot. Joints actuator using servo motors. Manipulator control system is used to adjust the angular position of each joint with CodeVisionAVR programming language that is sent in parallel to the motor driver so as to produce pulses to move the bike. Forward kinematics equation modeling using trigonometric equations. Forward kinematics modeling applications on the movement of the robot arm that is used to provide information about the value of the angle and the coordinates of each joint. Results of testing the hardware controlled by software to show the error (error) the movement of each joint is varied by between 0.06% - 2.567%.

scholarly journals End effector position calculation with the ANN for tapping machine

2021 ◽  
Vol 9 (3B) ◽  
Author(s):  
Gullu Akkas ◽  
◽  
Ihsan Korkut ◽  
Murat Tolga Ozkan ◽  
◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Position Control ◽  
Robot Manipulator ◽  
High Reliability ◽  
Future Research ◽  
Robot Arm ◽  
Labor Costs ◽  
End Effector ◽  
Cartesian Space ◽  
End Point

Nowadays, manufacturers give importance to the production of machines that allow for faster production, reduce labor costs, and minimize operation errors to meet the increasing demand. The search for such machines leads the manufacturing sector to automation. In this study, an automation-supported tapping machine prototype was manufactured. Kinematic equations were used for determining the location of the end effector in Cartesian space, whereas inverse kinematic equations were used for angular positions in joint space relative to positions in Cartesian space. Based on the results of the kinematic equations, the data obtained in certain positions were taught to the system through ANN. The position values for the angles known through the artificial intelligence algorithm were taught to the system. Then, the position coordinates to be reached by this manipulator, which has four degrees of freedom, for the intermediate position coordinate values through artificial neural networks (ANN) have been obtained. It is expected that the device controlled by artificial intelligence will not be affected by the variables in parameter or force changes requiring high working performance. With the control of the positions through ANN, it has been ensured that the position control of the tapping robot manipulator is predicted based on artificial intelligence techniques depending on the angle values of the limbs, and the robot is prevented from going to a position that is on a different trajectory. Accordingly, the robot arm has been made controllable with ANN techniques. With ANN modelling, the position of the end point to perform the tapping process was estimated with high reliability. For future research, a rough simulation was made to see whether the end point would go to a different position in space.

Motion Planning for a Redundant Robot Manipulator With Stochasticity in Joints

2014 ◽  
Author(s):  
Jaeyeon Lee ◽  
Wooram Park
Keyword(s):  
Stochastic Model ◽  
Motion Planning ◽  
Deterministic Model ◽  
Robot Manipulator ◽  
Robot Arm ◽  
Motion Error ◽  
End Effector ◽  
Redundant Robot ◽  
Planning Step ◽  
Rms Error

This paper concerns generation of motion for a redundant robot manipulator that shows stochastic behavior. Since a deterministic model is not sufficient to represent the motion of such manipulators, a stochastic model should be considered in the motion planning step. While classical approaches for robot control use the motion planning based on the deterministic model and then apply controls (e.g. the feedback control) to compensate the motion error, the new method developed in this paper considers the stochasticity of the system in the planning step for better results in terms of the motion error. This will lower the burden of the controller, resulting in more accurate control. This paper uses the stochastic model for the angle variables of robot joints. This gives the probability density function (pdf) for the position and the orientation of the robot end-effector. The goal of this paper is to find the optimal motion plan that enables the end-effector to follow a reference path with the minimized root-mean-square (RMS) error. To achieve this goal, the cost function that computes the RMS error is defined and then minimized with respect to the target angle values in the joint space. Using simulation of a 4DOF planar robot arm and a 7DOF spatial robot arm, we verify that the suggested method generates better motions than the classical inverse kinematics approach based on the deterministic model.

scholarly journals Method for Robot Manipulator Joint Wear Reduction by Finding the Optimal Robot Placement in a Robotic Cell

2021 ◽  
Vol 11 (12) ◽  
pp. 5398
Author(s):  
Tomáš Kot ◽  
Zdenko Bobovský ◽  
Aleš Vysocký ◽  
Václav Krys ◽  
Jakub Šafařík ◽  
...  
Keyword(s):  
Angular Velocity ◽  
Dynamic Simulation ◽  
Robot Manipulator ◽  
The Other ◽  
Robotic Arm ◽  
Robotic Cell ◽  
Wear Reduction ◽  
Fixed End ◽  
Robot Placement ◽  
Collaborative Robot

We describe a method for robotic cell optimization by changing the placement of the robot manipulator within the cell in applications with a fixed end-point trajectory. The goal is to reduce the overall robot joint wear and to prevent uneven joint wear when one or several joints are stressed more than the other joints. Joint wear is approximated by calculating the integral of the mechanical work of each joint during the whole trajectory, which depends on the joint angular velocity and torque. The method relies on using a dynamic simulation for the evaluation of the torques and velocities in robot joints for individual robot positions. Verification of the method was performed using CoppeliaSim and a laboratory robotic cell with the collaborative robot UR3. The results confirmed that, with proper robot base placement, the overall wear of the joints of a robotic arm could be reduced from 22% to 53% depending on the trajectory.

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