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检索条件"任意字段=3rd International Symposium on Control Engineering and Robotics, ISCER 2024"

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Tightly-Coupled Lidar-Based Lifelong Mapping using Wheels and a MEMS Gyroscope for Mobile Robots in Dynamic Environment 24

Tightly-Coupled Lidar-Based Lifelong Mapping using Wheels an...

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3rd international symposium on robotics, Artificial Intelligence and Information engineering, RAIIE 2024

作者： Hu, Lizhi Chen, Huilin Li, Xiang Lu, Wei Zhao, Yifan Hu, Songyu Navigation and Localization Algorithm Department Zhejiang HuaRay Technology Co. Lt. Hangzhou China Software Research and Development Center Zhejiang HuaRay Technology Co. Lt. Hangzhou China State Key Laboratory of Fluid Power and Mechatronic Systems College of Mechanical Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9798400718311

Localization and mapping technology of mobile robots is important in production and warehousing. The changing warehousing environment always result in poor accuracy and robustness of the mobile robot's localization. It is necessary to detect the degree of environmental changes and update the map. This paper proposes a novel lifelong mapping method fusing measurements from the lidar, wheels and a MEMS gyroscope, which can create a reliable map corresponding to the current working environment. Firstly, we use the wheels and gyroscopes measures for pre-integration to provide relative motion constraints, while integrating wheels and gyroscopes to provide initial pose for lidar matching. We also establish lidar odometry by submaps to provide another type of relative motion constraints. The absolute constraints are obtained by matching the lidar measurements with prior map. These three types of constraints are optimized in a factor graph. At the same time, during the process of updating the map, detect newly added artificial markers such as reflective columns or strips, and update them into the map timely. Then, in order to delete redundant lidar data keyframes for building map, we propose a determine redundancy method based on submaps. Finally, we propose a method for calculating the degree of map changes, which can update the map timely. Experimental results prove that our method can establish higher quality maps, optimize lidar external parameters timely during the mapping process, delete redundant lidar keyframes more efficiently, and update the current environmental map more accurately and timely. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Gyroscopes

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An Optimal control Based Trajectory Planning Method for Cooperative Merging Maneuvers 3

An Optimal Control Based Trajectory Planning Method for Coop...

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3rd international symposium on Intelligent robotics and Systems, ISoIRS 2023

作者： Wang, Qi Ge, Hao Duan, Xuting Zhou, Jianshan School of Transportation Science and Engineering Beihang University State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control State Key Laboratory of Air Traffic Management System and Technology Beijing China Nanjing Research Institute of Electronic Engineering State Key Laboratory of Air Traffic Management System and Technology Nanjing China School of Transportation Science and Engineering Beihang University State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China

ISBN: (纸本)9798350339963

Due to the prediction errors and diverse driving styles of surrounding vehicles, traffic congestion and even accidents can occur in the traffic bottleneck area where vehicles merge into the main road. To ensure that connected and automated vehicles (CAVs) can quickly and efficiently merge into the main road, this paper proposes a cooperative trajectory planning method based on optimal control for vehicle cut-in scenarios. A optimal control model is constructed, and a quintic polynomial is used to generate the initial solution of the optimal control problem to accelerate the solution process and improve the success rate. Finally, The obtained merging trajectory is then synchronized with the movement of vehicles on the main road to optimize their actions and ensure a safe merging process. Joint simulation with Robot Operating System (ROS) and RVIZ is utilized, and the results show that the proposed algorithm can quickly obtain cooperative results, the locally successful merging trajectory meets the requirements of smoothness and safety, and if the solution does not allow merging, the merging vehicle is instructed to terminate the execution. © 2023 IEEE.

关键词： Trajectories

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Prediction of milling surface roughness based on DGLCM and neural network 3

Prediction of milling surface roughness based on DGLCM and n...

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2023 3rd international Conference on Measurement control and Instrumentation, MCAI 2023

作者： Zhang, Chenghui Fang, Zaojun Lian, Hongyuan Zhang, Qiping Zhang, Chi Yang, Guilin Faculty of Mechanical Engineering & Mechanics Ningbo University Ningbo China Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Materials Technology Cas Ningbo China

With the manufacturing industry's increasingly automated and intelligent development, traditional workpiece roughness measurement methods can no longer meet the requirements for short time, high efficiency, and online measurement. Therefore, this article proposes a roughness evaluation model for vertical milling workpiece roughness measurement and improves upon the traditional Gray Level Co-occurrence Matrix (GLCM) method to achieve high accuracy and robustness in measuring milling surface roughness. First, the milled surface is illuminated by a coaxial light source, and an image is captured using an industrial camera and a telecentric lens. Then, four features of the image are extracted using the Direction Measure-based Gray Level Co-occurrence Matrix (DGLCM) to construct a feature descriptor. Finally, Finally, create an RBF network to predict surface roughness. Through experimental comparison with traditional GLCM feature extraction methods, our proposed feature extraction method has a prediction error of only 2.01%, which is superior to traditional methods. © Published under licence by IOP Publishing Ltd.

关键词： Surface roughness

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FEASIBILITY STUDY OF GNSS-ENABLED GCP MARKER FOR control ESTABLISHMENT FOR DRONE SURVEYING

FEASIBILITY STUDY OF GNSS-ENABLED GCP MARKER FOR CONTROL EST...

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2023 Philippine Geomatics symposium, PhilGEOS 2023

作者： Florin, A.F.P. Gomez, M.J.S. Mabaquiao, L.C.S. Ramos, R.V. Department of Geodetic Engineering University of the Philippines Diliman Quezon City Philippines

This study explores the potential of GNSS-enabled Ground control Point (GCP) markers as an alternative to traditional survey-grade receivers in observing GCPs for drone surveys. This is because an average drone flight and the observation period for rapid static are both 15 minutes. A GNSS-enabled GCP is already in the market through Propeller Aeropoints but is not available in the Philippines. Previous independent studies on the accuracy of such markers are limited as it is only focused on the accuracy. There are other considerations in using this technique such as the practicality of the marker, its usability with public Continuously Operating Reference Station (CORS) networks such as PAGeNet, and whether using it in conjunction with passive monuments will significantly affect the accuracy. The researchers designed and assembled a low-cost alternative using a u-blox module to determine the markers’ applicability and effectiveness. This study was limited to using three (3) GCPs to simulate the minimum number required to georeference in 2D. Accuracy remains an important criterion so observations will be compared with known positions. Three drone surveys were conducted to further evaluate its performance. The marker achieved 3rd Order geodetic control and demonstrated up to one standard deviation of error using statistical analysis. However, the lack of control points affected the accuracy observed in the checkpoints. This study focused on low-cost GNSS-enabled GCP marker since the commercial Aeropoints markers are not vailable in the country. Implementing this methodology in drone surveying could potentially increase survey efficiency in the Philippines and aid in the country's cadastral mapping efforts. © Author(s) 2024.

关键词： Drones

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FPGA Implementation of Neural Network Accelerator for PCB Defect Detection 3

FPGA Implementation of Neural Network Accelerator for PCB De...

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3rd international symposium on Computer engineering and Intelligent Communications, ISCEIC 2022

作者： Zhang, Jinzhou Zhang, Hui Zhao, Bingrui Liu, Jiaxuan Zhou, Xidong College of Electrical and Information Engineering Changsha University of Science & Technology Changsha China School of Robotics Hunan University Changsha China Department of Control Science and Engineering Hunan University Changsha China

ISBN: (纸本)9781510660298

With the rapid development of artificial intelligence, deep neural network (DNN) has been widely used in industrial defect detection, intelligent driving, medical research, etc. However, DNN is still limited in the implementation of edge computing and mobile devices due to its characteristics of high model complexity and high computing resource consumption. Therefore, we designed a neural network hardware accelerator based on Field Programmable Gate Array (FPGA) for printed circuit board (PCB) defect detection. In this paper, firstly, since structure re-parameterization can improve the network's accuracy without increasing the inference model's complexity, we introduce structure reparameterization to improve the YOLOv2 model and propose RepYOLOv2. Secondly, a low-bit quantization method based on integer type is adopted to quantify the model data to 6-bit. Then a specific convolutional computing module and neural network hardware accelerator are designed according to the characteristics of the model. Experimental results on Xilinx ZCU102 FPGA show that the real-time processing speed of the system reaches 2.12 FPS, the throughput is 68.53 GOP/s, and the power consumption is only 1.12 W. Compared with similar work, better performance is obtained. © The Authors. Published under a Creative Commons Attribution CC-BY 3.0 License.

关键词： Deep neural networks

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New Back-stepping Adaptive Optimal Excitation controller Based on STF 3

New Back-stepping Adaptive Optimal Excitation Controller Bas...

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3rd international symposium on Intelligent robotics and Systems, ISoIRS 2023

作者： Yang, Wenwen Gu, Zhifeng Jia, Xuebin Shang, Xinfei Wang, Biao You, Xuemin School of Electrical and Electrics Engineering Shijiazhuang Tiedao University Shijiazhuang China New Energy Industry Research Institute Tsinghua Taihao Sanbo Electric Motor Co. Ltd Shijiazhuang China Hebei Qianjin Machinery Factoryline Technical Department Shijiazhuang China

ISBN: (纸本)9798350339963

In this paper, in order to adapt to the nonlinear uncertain characters of the generator excitation system, resolve the large scale stability of the excitation system, by the backstepping design methods and the nonlinear state parameter estimation technology, a new nonlinear robust adaptive backstepping optimal excitation control (NRAOEC) method is proposed based on recursive design without linearization treatment. In the new control methods, the operating points of the system are tracked by STF estimate and calculated synchronously without sensors in the NRAOEC. Comparing with the EKF state estimation, STF state estimation methods can improve the estimation speed of the state observer, and adapt to the nonlinear characteristics of the excitation systems. In order to prove the new methods to be well for the excitation system stability, the Simulation experimental is conducted. The simulation resuls show comparing with traditional nonlinear robust adaptive back-stepping control method, NRAOEC is not only robust to the disturbance and adaptive to the uncertain parameters, but also can realize the optimal excitation control, improve convergence speeds of the state parameters by changing the values of weighting coefficients, and minimize the impact of disturbance by solving the LMI to obtain the optimal control law against the worst disturbance and improve the stability of the generating system. © 2023 IEEE.

关键词： State estimation

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A Compliance control Strategy for an Upper-Limb Rehabilitation Robot with a Quick and Real-Time Human-Robot Interactive Force Estimation 3

A Compliance Control Strategy for an Upper-Limb Rehabilitati...

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3rd international symposium on Intelligent robotics and Systems, ISoIRS 2023

作者： Li, Guoning Ye, Sijia Meng, Jingyan Zuo, Guokun Zhang, Jiaji Shi, Changcheng Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo China University of Chinese Academy of Sciences Beijing China Ningbo Cixi Institute of Biomedical Engineering Ningbo China

ISBN: (纸本)9798350339963

In order to improve the safety of rehabilitation training and estimate physical human-robot interaction(pHRI) force without force sensor, this paper designs a real-time interactive force learning controller in an End-Effector Type Robot. The adaptive sliding mode term in controller is used to solve the uncertainties in the robot modeling and inertial parameter measurements. The learning law term can estimate pHRI force. To investigate the performance of this controller, experiments were designed to repeat the tracking task on a circular trajectory. The result shows that this controller can make the tracking error and the estimate error of pHRI force gradually acquire a desired stability margin. The error of resultant force of pHRI between the estimating and the measuring by the force sensor is 2.87±2.50N. This controller enables the robot to exhibit high compliance and its estimation of the pHRI force takes less time and is more accurate. © 2023 IEEE.

关键词： controllers

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A MPGNN-Based Unsupervised Learning Framework for Power control in D2D Networks 3rd

A MPGNN-Based Unsupervised Learning Framework for Power Cont...

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3rd international Conference on Artificial Intelligence, robotics, and Communication, ICAIRC 2023

作者： Zhang, Yan He, Yucheng Zhang, Yu Xiamen Key Laboratory of Mobile Multimedia Communications Huaqiao University Xiamen362021 China

ISBN: (纸本)9789819721993

The Internet of Things (IoT) allows physical devices to be connected over wireless networks, and while device-to-device (D2D) communication has become a promising technology for IoT, traditional solutions for D2D resource allocation are often computationally complex and time-consuming. In order to improve the computational efficiency and improve the generalization performance of the algorithm, a large-scale power control unsupervised learning framework algorithm based on Message Passing Graph Neural Network (MPGNN) was proposed, which aims to maximize the weighting and rate of all D2D links. To achieve the above goals, we first model the topology of the wireless network as a graph model, define the channel matrix as the graph structure, and then model the objective function of the system as a loss function and train the model parameters in the MPGNN with the help of the unsupervised learning model. After offline training, each D2D link can obtain the optimal power control strategy in a distributed manner according to the channel state information (CSI). Simulation shows that compared with the classic algorithm based on optimization theory, Weighted Minimum Mean Square Error (WMMSE), the computational efficiency of the proposed algorithm is increased by more than 50 times when the number of users is 100 pairs. In addition, compared with the traditional neural network algorithm, deep neural network (DNN), the proposed algorithm improves the generalization ability of the system under the same parameter settings. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Message passing

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Motor Imagery Analysis of EEG Signals Using a Low-Cost Ankle Exoskeleton 3

Motor Imagery Analysis of EEG Signals Using a Low-Cost Ankle...

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3rd IEEE international Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2024

作者： Polo-Hortigüela, Cristina Gracia, Desirée I. Soriano-Segura, Paula Ortiz, Mario Iáñez, Eduardo Cavaliere-Ballesta, Carlo Azorín, José M. Miguel Hernández University of Elche Brain-Machine Interface Systems Lab Elche Spain Engineering Research Institute of Elche - I3E Miguel Hernández University of Elche Elche Spain Valencian Graduated School and Research Network of Artificial Intelligence - ValGRAI Valencia Spain

ISBN: (纸本)9798350378009

The combined use of a brain-machine interface (BMI) and a robotic device, such as an exoskeleton, is one of the state of the art techniques in neurorehabilitation. Among the control methods employed for BMIs, the paradigm of motor imagery is widely used. To achieve this control it is necessary to define an electroencephalographic (EEG) signal decoding algorithm for the extraction of optimal features. The latter is difficult due to the non-stationary character of the EEG signal and the artefacts that can interfere in it. This study focuses on the analysis and processing of EEG signals from two healthy subjects to develop an algorithm for the decoding of motor imagery (MI). As a method for feature extraction, PSD (Power Spectral Density) will be used. For this purpose, the Welch technique, which is an approach measure of the PSD, is applied. This algorithm has been tested for two electrode combinations. In addition, the EEG signals are conditioned by the movement generated in the foot due to an ankle exoskeleton used. This exoskeleton has been designed with a low-cost philosophy and allows dorsiflexion and plantar flexion movements. The result of the MI decoding algorithm for the first combination was an average accuracy value of 68.8% and for the second combination 75%, providing an important baseline for future research in this area. © 2024 IEEE.

关键词： Exoskeleton (robotics)

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Microchannel-based Droplet Generation Using Multiphase Flow: A Review 3

Microchannel-based Droplet Generation Using Multiphase Flow:...

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3rd international symposium on Advances and Innovation in Mechanical engineering, ISAIME 2022

作者： Raynaldo, K. Whulanza, Y. Irwansyah, R. Laboratory of Fluid Mechanics Department of Mechanical Engineering Faculty of Engineering Universitas Indonesia West Java Depok16424 Indonesia Research Center on Biomedical Engineering Universitas Indonesia West Java Depok16424 Indonesia

Microfluidics is a multidisciplinary field that allows for precise control of fluids at a micrometer scale, with the goal of generating encapsulated structures or droplets for specific purposes. However, producing monodispersed droplets remains a challenge, making it necessary for researchers to investigate optimal microchannel geometries and parameters for controlling droplet size. Channel-based geometries, including T-junction, flow-focusing, co-flowing, membrane, and step emulsification, are the most commonly used geometries, each with its own advantages and weaknesses. This literature review aims to highlight assessment methods of microfluidic device performance and physical phenomenon in droplet generation for each channel-based geometry, including recent findings by researchers. Output parameters such as microchannel geometries, flow patterns, and flow regime maps with interpretations can be used to evaluate the optimum input for generating droplets that are suitable for a certain application. With the COVID-19 pandemic affecting the world, there is an opportunity to use microfluidic devices to study SARS-CoV-2 and develop post-pandemic therapeutics. The next challenge in microfluidic device development is producing high-throughput double emulsion droplets with monodispersed size using optimum input parameters to satisfy the drug delivery purpose. © Published under licence by IOP Publishing Ltd.

关键词： Microfluidics

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