Coal and Gangue Recognition Method Based on Local Texture Classification Network for Robot Picking
Source abstract
Abstract
Coal gangue is a kind of industrial waste in the coal mine preparation process. Compared to conventional manual or machine-based separation technology, vision-based methods and robotic grasping are superior in cost and maintenance. However, the existing methods may have a poor recognition accuracy problem in diverse environments since coals and gangues’ apparent features can be unreliable. This paper analyzes the current methods and proposes a vision-based coal and gangue recognition model LTC-Net for separation systems. The preprocessed full-scale images are divided into n × n local texture images since coals and gangues differ more on a smaller scale, enabling the model to overcome the influence of characteristics that tend to change with the environment. A VGG16-based model is trained to classify the local texture images through a voting classifier. Prediction is given by a threshold. Experiments based on multi-environment datasets show higher accuracy and stability of our method compared to existing methods. The effect of n and t is also discussed.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Mineral Processing and Grinding · Belt Conveyor Systems Engineering · Metal Extraction and Bioleaching
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Software, Beijing University of Posts and Telecommunications, Beijing 100876, China
International School, Beijing University of Posts and Telecommunications, Beijing 100876, China
School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China
School of Mechanical & Electrical Engineering, Beijing Information Science & Technology University, Beijing 100192, China
Funding
National Key Research and Development Program of China · National Natural Science Foundation of China · BUPT innovation and entrepreneurship support program
References (23)
Show source-provided references
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