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检索条件"任意字段=2024 International Conference on Intelligent Robotics and Automatic Control"

共 5236 条记录，以下是81-90 订阅

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Design of intelligent Constant Temperature Foot Bath control System Based on STM32

Design of Intelligent Constant Temperature Foot Bath Control...

引用

2024 international conference on Computing, robotics and System Sciences, ICRSS 2024

作者： Ji, Siying Tan, Hanhong Teng, Yanfei Guangdong University of Science and Technology Dongguan523000 China

ISBN: (纸本)9798331511296

In the post-epidemic era, people are more aware of the possibility of novel coronavirus coexisting with human beings, so it is crucial to improve immunity. In the fast pace of life and work state, foot bath has become one of the ways for people to relax. In view of the current market traditional foot bath function is relatively simple, imperfect shortcomings, this paper designed a home intelligent constant temperature foot bath control system. The foot bath with STM32F103C8T6 as the control core, with WiFi communication module, temperature detection module, temperature control module, key control module, vibration module and OLED display module, etc., through the mobile phone APP or key operation can control intelligent constant temperature foot bath control system, can realize automatic constant temperature, remote control, vibration massage, timing reminder, and other functions. The design is practical and innovative, fully meeting the diversified needs of users for foot bath devices. © 2024 IEEE.

关键词： Coronavirus

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Garbage Image Classification Using Improved Inception-V3 Neural Network

Garbage Image Classification Using Improved Inception-V3 Neu...

引用

2024 international conference on intelligent robotics and automatic control

作者： Wang, Xiaohui Shi, Yaying Fu, Siyong Chifeng Univ Sch Phys & Intelligent Mfg Engn Chifeng Peoples R China Jingdezhen Univ Sch Mech & Elect Engn Jingdezhen Jiangxi Peoples R China Xinyu Univ ZTE Sch Commun & Informat Engn Xinyu Peoples R China

ISBN: (纸本)9798350389814;9798350389807

This paper presents an improved Inception-V3 model for garbage image classification aimed at facilitating intelligent garbage sorting through computer vision or mobile terminal applications. Initially, the iPhone-GARBAGE dataset of garbage images is constructed. Subsequently, the convolution blocks in the original Inception-V3 are replaced with new Inverted Bottleneck modules for richer feature expressions. Additionally, a Contextual Transformer module is added, enabling the model to discern more detailed object and scene semantics. The substitution of multi-scale pooling layers for the conventional maximum pooling layers further enhances the model's capability to recognize and retain features. Lastly, the integration of data augmentation and transfer learning strategies into the deep convolutional network empowers the recognition and classification of garbage images. Comparative experiments with different models under identical conditions are conducted. Results indicate that the improved Inception-V3 model achieves a classification accuracy of 96.20% and a test accuracy of 96.10%, surpassing other models. The proposed model demonstrates faster improvement rates and better convergence.

关键词： machine vision convolutional neural network inverted bottleneck contextual transformer garbage classification

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MDSTC: A Dynamic Approach to Multi-robot Coverage Path Planning 18

MDSTC: A Dynamic Approach to Multi-robot Coverage Path Plann...

引用

18th international conference on control Automation robotics and Vision

作者： Mo, Weimin Lin, Zhiyun Southern Univ Sci & Technol Sch Syst Design & Intelligent Mfg Shenzhen 518055 Peoples R China Southern Univ Sci & Technol Shenzhen Key Lab Control Theory & Intelligent Sys Shenzhen 518055 Peoples R China Peng Cheng Lab Shenzhen 518066 Peoples R China

ISBN: (纸本)9798331518509;9798331518493

Maximizing the efficiency of multi-robot systems is one of the primary objectives in solving the multi-robot coverage path planning (mCPP) problem. During coverage tasks, unexpected imbalances in the multi-robot systems, such as changes in speed, can lead to suboptimal utilization of the system's capabilities, subsequently reducing the efficiency of task execution. In this paper, we developed a multi-robot dynamic spanning tree coverage (MDSTC) algorithm, an online area-division-based approach that adjusts region allocation among robots based on their coverage status through an exchange-based mechanism to enhance multi-robot system efficiency. To validate the effectiveness of the proposed algorithm, we conducted extensive numerical simulations. The results demonstrate that our algorithm achieves a superior solution in scenarios where robot efficiency remains balanced, closely matching the performance of state-of-the-art mCPP methods. Furthermore, when differences in efficiency arise among the robots during task execution, the proposed algorithm provides a dynamic solution that enhances overall coverage efficiency.

关键词： Multipurpose robots

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Research on intelligent lane-changing model based on multi-intelligent reinforcement learning 6

Research on intelligent lane-changing model based on multi-i...

引用

6th international conference on robotics, intelligent control and Artificial Intelligence, RICAI 2024

作者： Fang, Jing Zhang, Yongjie Guangxi Vocational Normal University Guangxi Nanning China Key Laboratory of Application Technology of Intelligent Connected Vehicle Guangxi Vocational Normal University Education Department of Guangxi Zhuang Autonomous Region Guangxi Nanning China

ISBN: (纸本)9798331541699

S. Most of the traditional automatic driving behaviours are based on mathematical formulae or vehicle dynamics and kinematics models, which ignore the driver's perception and decision-making ability in the actual driving process, and the generated trajectories are very different from the actual lane-changing trajectories. In this paper, we adopt an automatic driving system based on multi-intelligence reinforcement learning to optimise the lane-changing decision of the vehicle by combining multi-intelligence reinforcement learning algorithms and avoiding the interference of inter-vehicle information interaction. In this way, the self-driving vehicle can have the functions of complex environmental perception, path planning and behavioural decision making. Combined with the highway mixed-flow environment scenario, the vehicle lane-changing behaviour model based on the HMM model is carried out for comparative experiments, and the results show that the lane-changing intention model based on multi-intelligence body reinforcement learning performs better in lane-changing detection accuracy and can be adapted to traffic scenarios with different traffic flow densities. © 2024 IEEE.

关键词： Reinforcement learning

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Research on Robot Motion Teaching Based on Human Pose Reconstruction Models

Research on Robot Motion Teaching Based on Human Pose Recons...

引用

2024 international conference on intelligent robotics and automatic control

作者： Zhang, Xuchong Ma, Xiaohui Lin, Yuquan Wang, Kui South China Univ Technol Sch Design Guangzhou Peoples R China Guangdong Inst Special Equipment Inspect & Res Foshan Peoples R China

ISBN: (纸本)9798350389814;9798350389807

The objective of this research is to explore a humanoid dual-arm robot motion teaching method that integrates human pose reconstruction technology, additionally, the study assesses the accuracy of the robot in replicating actions. Firstly, we employed an improved Denavit-Hartenberg (D-H) parameter method for kinematic modeling of the robot's configuration. Subsequently, we extracted motion data from various video sources using a human pose reconstruction model. After preprocessing the data, we optimized redundant degrees of freedom and applied the Jacobian iterative method for kinematic solving to replicate human actions observed in videos. Furthermore, we assessed the results of robotic action reproduction through two dimensions: positional error and action similarity. Experimental results indicate that the robot successfully reproduces various actions from different videos. However, factors such as video quality and background can affect model capture precision, thereby influencing the reconstruction effectiveness of certain movements. For humanoid-configured robots, after appropriate data processing, employing deep learning-driven human pose reconstruction algorithms enables rapid and cost-effective construction of a robotic motion library.

关键词： Video Demonstration Action Mapping Humanoid robotics

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Multi-Junction Traffic Light control System with Reinforcement Learning in Sunway Smart City

Multi-Junction Traffic Light Control System with Reinforceme...

引用

IEEE international conference on automatic control and intelligent Systems (I2CACIS)

作者： Lam, Hao Cheng Wong, Richard T. K. Jasser, Muhammed Basheer Chua, Hui Na Issa, Bayan Sunway Univ Sch Engn & Technol Dept Comp & Informat Syst Jalan Univ Bandar Sunway 47500 Selangor Darul Malaysia Sunway Univ Res Ctr Human Machine Collaborat HUMAC Sch Engn & Technol Jalan Univ Bandar Sunway 47500 Selangor Darul Malaysia Univ Aleppo Fac Informat Engn Aleppo Syria

ISBN: (纸本)9798350372113;9798350372106

This paper presents a reinforcement learning approach to address urban traffic congestion with traffic light control optimization. The proposed system leverages Q-learning and Markov Decision Processes (MDPs) to develop an adaptive control framework capable of adjusting traffic signal timings dynamically. A neural network model is employed to estimate Q-values, representing cumulative rewards for various control actions. The training process involves interactions between the agent and a simulated traffic environment using the Simulation of Urban Mobility (SUMO) tool. Experimental results showcase the efficacy of the RL-based approach in mitigating congestion and improving traffic flow. This work focuses on the case study of a network of junctions that contribute to the main traffic flow in the township of Bandar Sunway.

关键词： reinforcement learning q-learning Markov decision process traffic light control adaptive traffic light system

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Pump-valve Coordinated control of Robotic Arm Driven by Electro-hydraulic System 7

Pump-valve Coordinated Control of Robotic Arm Driven by Elec...

引用

7th international conference on Mechatronics, robotics and Automation

作者： Han, Xu Chen, Jikai Pan, Sheng Li, Xiaofan Luo, Xiang Ren, Dingwei Southeast Univ Sch Mech Engn Nanjing Peoples R China Jiangsu Prov Rehabil Ctr Persons Disabil Nanjing Peoples R China

ISBN: (纸本)9798350352481;9798350352474

This paper introduces a pump-valve coordinated control of robotic arm driven by electro-hydraulic system. Firstly, the system architecture of electro-hydraulic robotic arm is presented, and the models of the pump control as well as valve control parts are established. Secondly, the mechanism of pump-valve coordinated control is proposed. Thirdly, in order to resist unforeseeable disturbances in the system, a second-order linear automatic disturbance rejection controller (LADRC) is designed for the valve control subsystem. Finally, verification experiments are carried out. The experimental results show that the power consumption of the pump valve coordinated control system is only 56% of that of the ordinary valve control system, and has better dynamic performance.

关键词： Electro-hydraulic servo system Pump-valve coordinated control LADRC Energy-saving Dynamic performance

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Adaptive Impedance Modulation-Based control for Human-Robot Interaction 11

Adaptive Impedance Modulation-Based Control for Human-Robot ...

引用

11th IEEE international conference on Cybernetics and intelligent Systems (CIS) / 11th IEEE international conference on robotics, Automation and Mechatronics (RAM)

作者： Du, Liang Lv, JiYu Qiu, Limin Chen, Shouyan Guangdong Ind Polytech Univ Sch Mech & Elect Technol Guangzhou Peoples R China Guangzhou Univ Sch Mech & Elect Engn Guangzhou Peoples R China

ISBN: (纸本)9798350364200;9798350364194

Impedance control is commonly used to garantee the effciency and safety of physical human-robot interaction. Classic impedance control is not able to adaptivly modify impedance parameters according to dynamic enviroment. This paper used adaptive learning algorithm to modify parameters according human and enviroment variation. Model of robot and impedance control are established and corresponding experiments are conducted to verify the performancec of proposed approach. The simulation and experiment results indicated that the proposed approach can achieve a better convergence speed and robustness.

关键词： human robot interaction impedance control adaptive learning algorithm

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Comparison of the Performances between Fuzzy and Fuzzy PID Temperature controllers in Phototherapy Incubator for Infant Jaundice Treatment

Comparison of the Performances between Fuzzy and Fuzzy PID T...

引用

2024 international conference on intelligent robotics and automatic control

作者： Liang, Leyang Zhou, Miaoxian Li, Zupeng Xu, Guangming Lu, Bing-Yuh Huang, Ruilong Guangdong Univ Petrochem Technol Fac Automat Maoming Peoples R China Guangdong Univ Petrochem Technol Guangdong Prov Key Lab Petrochem Equipment Fault Maoming Peoples R China

ISBN: (纸本)9798350389814;9798350389807

Fuzzy control demonstrates remarkable flexibility in addressing nonlinear issues and formulating algorithms through an if-then rule pattern. However, a fuzzy controller requires a substantial number of fuzzy grades, leading to increase many rules for achieving higher accuracy. This study introduces an efficient Fuzzy-PID (FPID) controller designed to manage the degree of membership in the fuzzy inference system, specifically for temperature control in a phototherapy incubator. Comparative analyses of the performance of the fuzzy and FPID controllers were conducted in a computer simulation. The FPID controller exhibited significantly superior performance, notably reducing the time delay compared to the fuzzy controller. In the simulation, the delays for the FPID and PID controllers were approximately 0.5 and 5 seconds, respectively. The equivalent fine-tuning of the PID controller for the fuzzy logic controller is straightforward to implement and offers high performance in regulating the temperature of the incubator. Consequently, the simulation results provide valuable insights for the design of modern phototherapy incubators used in the treatment of infant jaundice.

关键词： fuzzy control temperature control infant jaundice PID control

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Distributed Resilient Frequency control for Distributed Energy Sources against High-density Misbehaving Agents 18

Distributed Resilient Frequency Control for Distributed Ener...

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18th international conference on control Automation robotics and Vision

作者： Li, Yutong Wang, Lili Wu, Xuyang Zhejiang Univ Coll Elect Engn Hangzhou Peoples R China Southern Univ Sci & Technol Sch Syst Design & Intelligent Mfg Shenzhen Peoples R China

ISBN: (纸本)9798331518509;9798331518493

This article studies the resilient leader-follower tracking problem for the frequency control of distributed energy sources(DESs), and focuses on scenarios with a high density of misbehaving agents. To tackle the problem, we propose a fully distributed resilient consensus protocol, which utilizes confidence weights to evaluate the level of trust among agents with a first-order filter and a softmax-type function. The protocol theoretically ensures that the system is uniformly ultimately bounded, even in the presence of high-density misbehaving agents (that is, for each follower, it can have more misbehaving neighbors compared to normal neighbors). We also demonstrate the fast practical convergence of the proposed protocol with a simulation for a frequency control problem of DESs. Our study is a significant step towards enhancing the reliability and stability of modern power systems.

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