Simulation of a 3-DOF Robotic Arm Pick and Place Task Based on Inverse Kinematics

This paper proposes a simulation method for grasping and placing a 3-DOF robotic arm based on inverse kinematics.Through the MATLAB GUI, the user enters target coordinates, computes the joint angles by the inverse kinematics geometric approach and simulates the motion path to achieve the task operation.In this approach, the robotic arm can reach specified positions precisely, which reduces complexity and error.The position error is calculated through a comparison of the target and the actual position.The simulation results show that the robot arm achieves a small average error across all five experimental groups.The maximum error remains within a reasonable range, which confirms the accuracy of the method in grasping and placing tasks.

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Publication Details

Journal
Proceedings of International Conference on Artificial Life and Robotics
Published
2025-02-13
DOI
https://doi.org/10.5954/icarob.2025.os4-3
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Simulation of a 3-DOF Robotic Arm Pick and Place Task Based on Inverse Kinematics

Suyu Mei, Miao Zhang
Proceedings of International Conference on Artificial Life and Robotics
Robot Manipulation and Learning
article

Simulation of a 3-DOF Robotic Arm Pick and Place Task Based on Inverse Kinematics

Suyu Mei, Miao Zhang
article en

Abstract

This paper proposes a simulation method for grasping and placing a 3-DOF robotic arm based on inverse kinematics.Through the MATLAB GUI, the user enters target coordinates, computes the joint angles by the inverse kinematics geometric approach and simulates the motion path to achieve the task operation.In this approach, the robotic arm can reach specified positions precisely, which reduces complexity and error.The position error is calculated through a comparison of the target and the actual position.The simulation results show that the robot arm achieves a small average error across all five experimental groups.The maximum error remains within a reasonable range, which confirms the accuracy of the method in grasping and placing tasks.

Proceedings of International Conference on Artificial Life and RoboticsVol. 30
Tianjin University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 73%
Robot Manipulation and Learning
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