Research on Recognition, Positioning and Grasping of Robotic Arms Based on an Improved ORB Algorithm

Aiming at the problem that the traditional ORB algorithm is difficult to realize the real-time and accurate grasp of the object by the robotic arm equipped with the binocular stereo vision, a robotic arm recognition and grasping method based on an improved ORB algorithm was proposed. Firstly, the improved ORB algorithm was used to identify the target, and then the target was positioned according to the binocular stereo vision optical axis parallel model. Then, the mathematical model of the robotic arm was established by using the standard D-H parameter method, and the inverse kinematics was solved. Finally, the obtained drive angles of each joint of the robotic arm were transmitted to the control end of the system. The end effector of the robotic arm was driven to complete the grasp of the target. The results show that compared with the traditional ORB algorithm, the improved ORB algorithm in this study can improve the speed and accuracy of target recognition and positioning, and effectively improve the real-time and accurate grasping of the robotic arm.

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-10-01
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
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article

Research on Recognition, Positioning and Grasping of Robotic Arms Based on an Improved ORB Algorithm

SHILAP Revista de lepidopterología
Robot Manipulation and Learning
article

Research on Recognition, Positioning and Grasping of Robotic Arms Based on an Improved ORB Algorithm

article en

Abstract

Aiming at the problem that the traditional ORB algorithm is difficult to realize the real-time and accurate grasp of the object by the robotic arm equipped with the binocular stereo vision, a robotic arm recognition and grasping method based on an improved ORB algorithm was proposed. Firstly, the improved ORB algorithm was used to identify the target, and then the target was positioned according to the binocular stereo vision optical axis parallel model. Then, the mathematical model of the robotic arm was established by using the standard D-H parameter method, and the inverse kinematics was solved. Finally, the obtained drive angles of each joint of the robotic arm were transmitted to the control end of the system. The end effector of the robotic arm was driven to complete the grasp of the target. The results show that compared with the traditional ORB algorithm, the improved ORB algorithm in this study can improve the speed and accuracy of target recognition and positioning, and effectively improve the real-time and accurate grasping of the robotic arm.

SHILAP Revista de lepidopterología
Openalex Percentile: Top 55%
Robot Manipulation and Learning
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Research on Recognition, Positioning and Grasping of Robotic Arms Based on an Improved ORB Algorithm · SHILAP Revista de lepidopterología (2024) | TGRS Research Map | TGRS