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Intelligent Garbage Recycling: Design and Implementation Exploration of Automatic Classification System

Meteorological and Environmental Research 2024年第2期15卷 37-39,43页

作者： Dexian HUANG Binjun GAN Environmental Sanitation Station in Wuming District of Nanning City Nanning 530100China Smart Agriculture College Yulin Normal UniversityYulin 535000China

This paper introduces an intelligent waste recycling automatic classification system,which integrates sensors,image recognition,and robotic arms to achieve automatic identification and classification of *** system monitors the composition and properties of waste in real time through sensors,and uses image recognition technology for precise classification,and the robotic arm is responsible for grabbing and *** design and implementation of the system have important practical significance and application value,and help promote the popularization and standardization of waste *** paper details the system s architecture,module division,sensors and recognition technology,robotic arm and grabbing technology,data processing and control system,and testing and optimization *** results show that the system has efficient waste recycling efficiency and accuracy in practical applications,bringing new development opportunities to the waste recycling industry.

关键词： Waste classification and recycling Sensors Image recognition robotic arms Convolutional neural networks

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Dynamic Coordination of Uncalibrated Hand/Eye robotic System Based on Neural Network

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Journal of Systems Engineering and Electronics 2001年第3期12卷 45-50页

作者： Su, J. Pan, Q. Xi, Y. Institute of Automation Shanghai Jiaotong University Shanghai 200030 China

A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation results show that this method can drive the static tracking error to zero quickly and keep good robustness and adaptability at the same time. In addition, the algorithm is very easy to be implemented with low computational complexity.

关键词： Adaptive algorithms Computational complexity Computer simulation Coordinate measuring machines Error detection Mathematical models Neural networks robotic arms Robustness (control systems) Stereo vision

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A DoS Attacks Detection Aglorithm Based on Snort-BASE for robotic Arm Control Systems

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Journal of Computer and Communications 2022年第4期10卷 1-13页

作者： Nana Li Yong Wang Pengfei Shen Shuangfei Li Lin Zhou College of Science Shanghai University of Electric Power Shanghai China IBM (China) Investment Co. Ltd. Shanghai China Shanghai Cloud Sword Information Technology Co. Ltd Shanghai China

In response to the frequent safety accidents of industrial robots, this paper designs and implements a safety detection system for robot control. It can perform real-time security detection of robot operations on industrial production lines to improve the security and reliability of robot control systems. This paper designs and implements a robot control system based Snort-BASE for real-time online detection of DoS attacks. The system uses a six-degree-of-freedom robotic arm as an example, uses Snort to record the network communication data of the robot arm control system in real time, and filters the network traffic through self-defined rules, and then uses the BASE analysis platform to achieve security analysis of the network traffic. The solution verifies the effectiveness of online real-time detection of attacks and visualisation of attack records by designing simulated robotic arm and real robotic arm attack experiments respectively, thus achieving the security of network communication of the robot remote control system.

关键词： robotic arms Remote Control Systems Cyber Attacks BASE Snort Security Protection

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