A Novel Disassembly Strategy of Hexagonal Screws Based on Robot Vision and Robot-Tool Cooperated Motion
Source abstract
Abstract
Disassembly plays an important role in the production process. Screw automatic unfastening guided by a robot has been widely used in the fields of industrial manufacturing and maintenance. Different from the previous studies that have used a flexible effector and expensive sensors, this paper presents a novel unfastening strategy based on robot vision for a hexagonal screw with an arbitrary loose state. In a robotic system, an industrial camera and a servo unfastening tool are installed at a robotic end-effector. The main contributions of this work are as follows. A camera pose adjustment method is proposed to obtain high-quality images of a target screw. The hexagonal screw pose calculation method based on the geometric analysis is developed to complete the screw–tool engagement. The cooperated motion of a robot and an unfastening tool is planned for the screw unfastening action. The effectiveness of the proposed control strategy is verified by experiments, and the influence of the motion speed on the unfastening quality is analyzed using the torque data collected by the unfastening tool. The analysis results can provide a significant foundation for the motion parameter selection in the proposed strategy.
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Research context
OpenAlex topics: Robotic Mechanisms and Dynamics · Robot Manipulation and Learning · Manufacturing Process and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing 100124, China
Machinery Industry Key Laboratory of Heavy Machine Tool Digital Design and Testing Technology, Beijing University of Technology, Beijing 100124, China
Key Laboratory of CNC Equipment Reliability, Ministry of Education, School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130012, China
Funding
the National Natural Science Foundation of China · Scientific Research Project of Beijing Educational Committee · China Postdoctoral Science Foundation · Beijing Nova Program Interdisciplinary Cooperation Project
References (35)
Show source-provided references
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