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检索条件"任意字段=5th International Conference on Informatics in Control, Automation and Robotics"

共 2266 条记录，以下是551-560 订阅

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Flight control of a Multicopter using Reinforcement Learning 20th

Flight Control of a Multicopter using Reinforcement Learning

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20th IFAC conference on Technology, Culture, and international Stability (TECIS)

作者： D'Apolito, Francesco Sulzbachner, Christoph AIT Austrian Inst Technol Ctr Vis Automat & Control Seibersdorf Austria

Machine Learning, and in particular Reinforcement Learning, is a persistent trend in automation and robotics in recent years. Many researchers worldwide are developing intelligent controllers using Reinforcement Learning techniques. this paper aims to present a proof-ofconcept Reinforcement Learning flight controller for a multicopter. the agent has been trained in the Airsim simulation environment to achieve stable flight conditions by controlling its roll, pitch, yaw and throttle. After training, the agent has been tested on the same environment to prove its ability to maintain stable flight conditions while following a determined route. Copyright (C) 2021 the Authors.

关键词： Artificial Intelligence and Applications Intelligent Systems and Applications robotics and Handling Devices Models and Simulation Mechatronic Systems and robotics

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5th international conference on robotics and Machine Vision, ICRMV 2021

5th International Conference on Robotics and Machine Vision,...

引用

2021 5th international conference on robotics and Machine Vision, ICRMV 2021

the proceedings contain 12 papers. the topics discussed include: vision and UWB-based anchor self-localization system for UAV in GPS-denied environment;application of driving style recognition in the shift control of a two-speed DCT for pure electric vehicles;vision-based bicycle and motorcycle detection using a YOLO-based network;transfer learning adaptive facial attractiveness assessment;design of projection optical system for 3D defect detection on PCB;a modification method based on U-net for the distorted pseudo edge of aerial initial orthophoto;augmentation on CNNs for handwritten digit classification in a small training sample size situation;and de-based algorithm for solving the inverse kinematics on a robotic arm manipulators.

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Research on water quality prediction method based on AE-LSTM 5

Research on water quality prediction method based on AE-LSTM

引用

5th international conference on automation, control and robotics Engineering, CACRE 2020

作者： Zhang, Huiqing Jin, Kemei Beijing University of Technology School of Automation Department of Informatics Beijing China

ISBN: (纸本)9781728198880

Aiming at the traditional prediction methods of related parameters that affect water quality, they usually only consider the temporal characteristics of the related parameters of water quality and ignore the problem that water quality changes are multivariate related, A prediction method of spatiotemporal correlation water quality parameters based on automatic encoder (AE) dimensionality reduction and long and short time memory (LSTM) neural network is proposed. Firstly, considering that water quality parameter changes have obvious time characteristics, a time series prediction model of water quality parameters is established based on LSTM. Secondly, considering that the water quality changes have multiple correlations, the upstream water quality will also affect the downstream water quality. If all the water quality parameters of the upstream station are added to the prediction model, redundant features will reduce the accuracy of parameter prediction. therefore, the automatic encoder is used to reduce the dimensionality of the relevant parameters. Finally, the data set of Lang fang Water Quality Automatic Monitoring Station is applied to monitor the effectiveness of the method. By predicting the concentration of total phosphorus (TP) and total nitrogen (TN), the method is found to have better prediction accuracy and robustness. © 2020 IEEE.

关键词： Long short-term memory

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the Effect of Feature Selection on Automatic Sleep Stage Classification Based on Multichannel EEG Signals 5

The Effect of Feature Selection on Automatic Sleep Stage Cla...

引用

5th IEEE international conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2021

作者： Kartika Delimayanti, Mera Laya, Mauldy Reza Faisal, Mohammad Fitri Naryanto, Rizqi Satou, Kenji Politeknik Negeri Jakarta Department Of Computer And Informatics Engineering Depok Indonesia Lambung Mangkurat University Department Of Computer Science Banjarbaru Indonesia Universitas Negeri Semarang Department Of Mechanical Engineering Semarang Indonesia Kanazawa University Institute Of Science And Engineering Kanazawa Japan

ISBN: (纸本)9781665401968

When diagnosing and treating sleep disorders, the manual classification of sleep stages is a time-consuming but crucial step, and the automation of this process has been a focus of recent research. Many kinds of research have been conducted on the automation of sleep stage classification. In this paper, we proposed the effect of feature selection on an automated system based on EEG signals, which was then followed by classification using various supervised classifiers such as Random Forest and SVM. the high dimensional FFT features were used to extract the characteristics of EEG for the classification of sleep stages. the EEG dataset is used from the Sleep-EDF dataset, which is freely available. the accuracy as the performance evaluator on the Random Forest model had gained the best value on 95.93%, 90.41%, 87.91%, 86.92%, and 84.86% and the SVM model reached 96.63%, 91.27%, 88.90%, 87.94%, and 87.94% for 2-6 state classification. Finally, in this proposed research the feature selection phase affects the model's accuracy. © 2021 IEEE.

关键词： Support vector machines

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Design of Directional Bird Dispersal Device in Substation Based on Infrared Sensing

Design of Directional Bird Dispersal Device in Substation Ba...

引用

robotics, control and automation Engineering (RCAE), international conference on

作者： Hanwu Luo Shikuan Chen Wenzhen Li Fang Li Yifeng Song Fengren Jing Zhenyu Yang East Inner Mongolia Electric Power Company Limited. Inner Mongolia China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781665459419

ISBN: (纸本)9781665459426

In order to reduce the impact of bird activities on the operation of power equipment, important power stations such as substations and converter stations are equipped with dispelling birds devices that can continuously output acoustic, optical and electrical signals for dispelling birds. However, due to the lack of target orientation for dispelling birds, birds can quickly produce adaptability, resulting in a significant decline in the effect of dispelling birds. In this paper, a directional dispersal device for substation birds based on infrared sensing is designed for directional aiming dispelling birds. Firstly, an improved image template matching method is used to complete the identification and location of bird targets. then bird's directional tracking and dispersion control algorithm based on PID is proposed. Finally, the experiment proves that the device has the characteristics of high positioning accuracy and fast-tracking speed for the dispersal of birds, which can quickly and effectively dispel moving birds accurately.

关键词： Substations Target tracking Target recognition Image matching Birds Robot sensing systems Optical imaging

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Fuzzy Logic and Neural Network-Based Intelligent control System for Quadruped Robot on Extreme Terrain 23

Fuzzy Logic and Neural Network-Based Intelligent Control Sys...

引用

23rd international conference on control, automation and Systems, ICCAS 2023

作者： Jeon, Jinwoo Jeong, Myungwoo Myung, Hyun School of Electrical Engineering KI-Robotics Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of

ISBN: (纸本)9788993215274

the quadruped robot has the advantage of having a high degree of freedom of motion. therefore, it has been used in various robot applications such as exploration. However, the quadruped robot is not easy to control due to the large number of joints. Existing control methodologies using proportional-integral-differential (PID) or model predictive control show decent performance on uniform terrain. However, the control performance is degraded in the extreme terrain where significant non-linear disturbance occurs. To tackle this problem, we propose FLONIC-Q: fuzzy logic and neural network-based intelligent control system for quadruped robots on extreme terrain. the proposed system includes high-level and low-level control using fuzzy logic and machine learning to deal with disturbances in extreme terrain. As demonstrated in the experiments, the proposed method performs superior to existing system response methods regarding absolute trajectory error and time analysis in various trajectory types. © 2023 ICROS.

关键词： Robot applications

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Artificial Intelligence and Machine Learning-Based Systems for controlling Medical Robot Beds for Preventing Bedsores

Artificial Intelligence and Machine Learning-Based Systems f...

引用

international conference on Contemporary Computing and informatics (IC3I)

作者： R Jaichandran Srikanth Rayavarapu Archana Ravindra Salve Manikandan Rajagopal G.N.R. Prasad Iskandar Muda Vinayaka Mission's Research Foundation Aarupadai Veedu Institute of Technoloyg India Liverpool John Moores University United Kingdom Indira College of Engineering and Management India School of Business and Management Christ Deemed to be University India Chaitanya Bharathi Institute of Technology India Universitas Sumatera Utara Indonesia

Artificial Intelligence is one of the most important technologies of the modern world which is continuously changing the dimensions of almost every sector. AI and IoT have together resulted in multiple outstanding technological innovations which have also impacted the healthcare sector massively. this study has critically focused on the role of AI and robotics in the treatment outcomes for patients. this study has done deep research regarding the role of automated beds in reducing pressure ulcers or bed sores among patients who are recovering from any chronic disease. this entire study has secondary qualitative data collection for analyzing the design and microcontroller systems in automated beds. this has provided a detailed data analysis with relevant equations and tables for reaching its proposed outcomes.

关键词： Industries Technological innovation Medical robotics Medical devices Service robots Microcontrollers Medical services

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Research on Gait Recognition of Exoskeleton Robot Based on DTW Algorithm 21

Research on Gait Recognition of Exoskeleton Robot Based on D...

引用

5th international conference on control Engineering and Artificial Intelligence, CCEAI 2021

作者： Wang, Hao Zhang, Rui Li, Zhijun College of Automation Wuhan University of Technology Wuhan China

ISBN: (纸本)9781450388870

the control strategy of exoskeleton robots is currently a hot research topic at home and abroad. How to accurately recognize human gait and improve the real-time performance of the system has always been the main research direction in this field. First, a human gait recognition program is designed, mainly, the human gait information is collected through the sensor, and then the S-G filter is used to preprocess the gait data, then the RLS algorithm is used to predict the gait data, and finally the DTW algorithm is used for Human gait phase recognition. then, the realization principle of the DTW algorithm is introduced, and corresponding improvement methods are proposed for the shortcomings of the algorithm. Finally, the gait phase recognition test of the human body is carried out on the DTW algorithm before and after the improvement. the experimental results show that compared with the traditional DTW algorithm, the improved DTW algorithm has a certain enhancement in recognition rate and real-time performance. © 2021 ACM.

关键词： Exoskeleton (robotics)

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RDDS: Road Disease Detection Model Based on YOLOv5

RDDS: Road Disease Detection Model Based on YOLOv5

引用

IEEE international conference on Cyber Technology in automation, control, and Intelligent Systems

作者： Zhiqiang Han Jun Gong Yu Qiao School of Vehicle and Transportation Engineering Taiyuan University of Science and Technology Taiyuan China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

the utilization of intelligent vehicles for detecting road anomalies has become a relatively common phenomenon. the existing road disease detection workload is large, the robustness is not high, and small diseases are easily ignored, which brings huge challenges to road disease detection. A road disease detection model named RDDS based on YOLOv5 is proposed. Based on the YOLOv5 algorithm, we incorporate Transformer encoder blocks into the head part to form Transformer Prediction Heads (TFE), expanding their number to four. this enhancement aims to improve the model's capability to detect small targets and road diseases of different scales. In addition, we introduce the convolutional block attention model (CBAM) to make the network pay more attention to important channels and spatial locations, thereby improving the performance and generalization ability of the model. Aiming at the problems of low resolution and insufficient data volume in current road disease data sets, we propose a new road disease detection data set RDDSC. Finally, we conducted experiments on the RDDSC data set. the experimental results showed that compared with the original YOLOv5, the RDDS parameters increased slightly, while the detection accuracy was significantly improved. Compared with existing detection algorithms, RDDS has obvious advantages in road disease detection.

关键词： YOLO Accuracy Roads Predictive models Transformers Prediction algorithms Robustness Maintenance Spatial resolution Diseases

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Helical SMA Actuator based Artificial Muscle and Arm with Sliding Mode control 2021

Helical SMA Actuator based Artificial Muscle and Arm with Sl...

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5th international conference of the robotics Society on Advances in robotics, AIR 2021

作者： Karmakar, Sourav Gaddam, Vineeth Kim, Jaeseok Mishra, Anand Kumar Sarkar, Abhishek International Institute of Information Technology Hyderabad And Robotics Research Center India Scuola Superiore sant'Anna Pisa Italy Cornell University Newyork United States BITS-Pilani Hyderabad Campus India

ISBN: (纸本)9781450389716

Shape Memory Alloy (SMA) wire actuator contracts or expands in response to heat due to its mechanical (NiTi) property. this paper is about the control perspective of light weight artificial muscle arm based on helical SMA actuator. the Arm is structured around the idea of simplicity and modularity. the post decomposition of the arm dynamics into position and force subspaces, Sliding Mode control is utilized with the end goal that time taken to reach the equilibrium point from any initial state is guaranteed to be finite time. this setup presents a light weight (70 g) and noiseless operation with a maximum payload of 64 g which is noteworthy when compared to the weight of SMA based artificial muscle and the arm. © 2021 ACM.

关键词： Mechanical actuators

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