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检索条件"任意字段=3rd International Conference on Robotics and Control Engineering, RobCE 2023"

共 3888 条记录，以下是201-210 订阅

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Research on Objectives Recognition of robotics based on Convolutional Neural Network 3

Research on Objectives Recognition of Robotics based on Conv...

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3rd international conference on Electronic Information engineering and Computer Science, EIECS 2023

作者： Ren, Guanzhu Zhao, Yichen Wu, Zhengfeng Li, Pengwei Mi, Kaiyu Taiyuan University of Technology College of Wollongong Engineering Taiyuan China Jinzhong China Taiyuan University of Technology College of Mechanical and Transportation Engineering Taiyuan China

ISBN: (纸本)9798350316674

Recently, robotics has widely utilized in tremendous applications including traffic transportation, medical treatments, power system and virtual environment. These applications are almost based on the vision system, which is consisted by detection sensors and cameras. However, existing recognition methods are concentrated on the precision of machine learnings under the ideal setups and ignored the complex environment for robotics. In this paper, we simulate the realistic robotics sensors with non-complete input images and propose a novel convolutional network without redundancy neural layers. Indeed, an attention mechanism is established to enhance the recognition accuracy of proposed framework. Finally, we evaluate our model with existing objectives identification learning methods in the identical testing configurations. From our extensive experiment results and analysis, we can conclude that the proposed model can achieve the objectives recognition in complex robotics scenario with acceptable recognition accuracy and reasonable computation costs. © 2023 IEEE.

关键词： Attention mechanism Convolutional neural network Objectives recognition robotics

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2018 3rd international conference on robotics and Automation engineering, ICRAE 2018

2018 3rd International Conference on Robotics and Automation...

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2018 3rd international conference on robotics and Automation engineering, ICRAE 2018

ISBN: (纸本)9781538695944

The proceedings contain 52 papers. The topics discussed include: design of a soft robot using pneumatic muscles for elbow rehabilitation;remote sensing images recognition by deep convolutional neural networks;challenges of dynamic environment for visual-inertial odometry;sensor fault tolerant algorithm for 7.2nm class SPMSM applied electro-hydraulic power steering system for medium and heavy commercial vehicle;an improved method of 3D scene reconstruction based on SfM;menu control and functionalities of 3D digital oscilloscope;multi-view clustering: a brief review;remote control and tracking dual mode smart suitcas;and a novel hybrid path planning algorithm at macroscopic level for autonomous climbing robot.

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Deep Learning Based Semantic Labelling of 3D Point Cloud in Visual SLAM 3

Deep Learning Based Semantic Labelling of 3D Point Cloud in ...

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3rd international conference on Automation, control and robotics engineering (CACRE)

作者： Qi, Xuxiang Yang, Shaowu Yan, Yuejin Natl Univ Def Technol State Key Lab High Performance Comp Changsha 410073 Hunan Peoples R China Natl Univ Def Technol Coll Comp Changsha 410073 Hunan Peoples R China

Three-dimensional (3D) point cloud understanding is important for autonomous robots. However, point clouds are normally irregular and discrete. It is challenging to obtain semantic information from them. In this paper, we present a method to build a dense semantic map, which utilizes both two-dimensional (2D) image labels and 3D geometric information. The dense point cloud is built by using a state-of-the-art RGB-D SLAM system. It is further segmented into meaningful clusters using a graph-based method. Then, image keyframes during the SLAM process are used to extract semantic image labels by a convolution neural network (CNN). Finally, these semantic labels are projected to the point cloud clusters to achieve a 3D dense semantic map. The effectiveness of our method is validated on a popular public dataset.

关键词： Graphic methods

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Auto-segmentation of Lung in CT Image Series Based on Level Set Method with Prior Knowledge 3

Auto-segmentation of Lung in CT Image Series Based on Level ...

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2017 3rd IEEE international conference on control Science and Systems engineering (ICCSSE)

作者： Rui Liang Xue Jiao Chen Jian Xun Zhang Shool of Information Technology Engineering Tianjin University of Technology and Education Institute of Robotics and Automatic Information System Nankai University

ISBN: (纸本)9781538604854

With development of medical image processing, more and more cancers are diagnosed and treated with assistance of computer, especially lung cancer. Extracting lung from CT image series is usually the first step. Hundreds of CT images slow down the processing. As to clinical applications, the accuracy and efficiency is crucial. We proposed and realized an auto-segmentation of lung in CT image series based on level set method with prior knowledge. Firstly, we autosegmented one CT image with LBF method. Secondly, we extracted the lung contour from the segmentation with region grow and feature selection. In the end, we extracted the lung contour of the next CT image with DRLSE method. The previous lung contour was set to be the initial contour to ensure the accuracy and efficiency. The experiment results proved that our approach is more stable and faster. It spent only about 67% of the time that LBF and DRLSE did.

关键词： auto-segmentation Lung Contour LBF DRLSE

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Research on The control System of The Friendly Walking Assistant Robot for The Elderly 3

Research on The Control System of The Friendly Walking Assis...

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3rd international conference on Automation, control and robotics engineering (CACRE)

作者： Wei, Xiaojuan Northwest Minzu Univ Sch Elect Engn Lanzhou 730124 Gansu Peoples R China

With the intensification of aging population, medical and social insurance system is facing up with the unprecedented pressure. Most of old people need nursing and care. On the one hand, it needs expensive expenditure and manpower. On the other hand, living quality of old people in degree of freedom is greatly reduced. The problem of helping old people to walk has become a great social problem. The self-adaption coordination control of robot is an important indicator of walking assistant robot for the elderly and also the precondition to support and protect old people and the disabled. In order to realize the control of direction for walking assistant robot and get the smaller turning radius and more flexible movement, this paper studied a dual-motor differential control method to realize forward, backward, and cornering of robot. Finally, the experimental results show that the control system of the friendly walking assistant robot for the elderly is rational and feasible, and the designed control system is stable and reliable.

关键词： Robots

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The Leader-Follower Joint Space Synchronous Impedance control for Coordinated Operation in Nuclear Industry 3

The Leader-Follower Joint Space Synchronous Impedance Contro...

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3rd international conference on Computer, control and robotics, ICCCR 2023

作者： Zhao, Xiaoyu Tang, Yuyao Yang, Yapeng Lv, Qi China Institute for Radiation Protection Nuclear Emergency and Nuclear Safety Department Taiyuan China

ISBN: (纸本)9781665492126

Coordinated operation is a common task for the dual-Arm robot system in nuclear industry, and the trajectory tracking performance and inner torque are both important indications for the coordinated operation. However, the radiation affects the application of end force/torque sensor and it is practicable to compromising the indications in the joint space. In this paper, leader-follower joint space synchronous impedance control is proposed to compromise the two indications. The dual-Arm system is controlled by the leader-follower mode and controller is designed to satisfy the pose and force constraints. Simulation is carried out and the results show considerable performance. © 2023 IEEE.

关键词： Nuclear industry

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Joint Robot and Aircraft Carriers Combinatorial Systems in the Sea in 5G OGCE 3

Joint Robot and Aircraft Carriers Combinatorial Systems in t...

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3rd international conference on robotics and Automation engineering (ICRAE)

作者： Lu, Zhi Wany, ZhongFeng Lu, Yi Yuan, Mingzhe Tianjin Univ Technol & Educ Sch IT & Engn Tianjin 300222 Peoples R China Chinese Acad Sci Shenyang Inst Automat Shenyang 110016 Liaoning Peoples R China

ISBN: (纸本)9781538695944

Based on the fifth generation of mobile communication (5G), 5G open grid computing environment (5G OGCE), in order to adapt to "civil-military integration strategy" in region from deep sea to space, at the same time to meet the needs of ocean engineering development, a joint (connecting or docking-and-berthing) robot and aircraft carriers combinatorial systems are presented in this paper, the aim of which is to, (1) achieve aircraft carrier combinatorial systems jointed dynamically by double aircraft carriers, or more ships and aircraft carriers, providing the new runway of 600 meters long taking off and landing aircraft in the sea;(2) integrate unmanned aircraft carriers (and manned aircraft carriers) to take off and land the sixth generation strike fighter or unmanned stealth fighter;(3) combine the aircraft carrier and new production systems of ocean engineering, including polar icebreaker, underwater rare earth mining, combustible ice mining, underwater power generation and so on;(4) support the development of sea wave energy, offshore power generation plant and weather radar forecasting platform, and the launch and recovery of offshore rockets. By using distributed control cloud architecture in 5G OGCE, large passenger aircraft taking off and landing at 600 meters runway in aircraft carriers combinatorial systems can be realized.

关键词： joint (connecting) robot hand type door robot distributed control cloud architecture aircraft carriers combinatorial systems 5G OGCE distributed artificial intelligence (Distributed AI) software architecture and engineering

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Model-Free Recurrent Reinforcement Learning for AUV Horizontal control 3

Model-Free Recurrent Reinforcement Learning for AUV Horizont...

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3rd international conference on Automation, control and robotics engineering (CACRE)

作者： Huo, Yujia Li, Yiping Feng, Xisheng Chinese Acad Sci Shenyang Inst Automat State Key Lab Robot Shenyang 110016 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

In this paper, aiming at the problems of 2-DOF horizontal motion control with high precision for autonomous underwater vehicle(AUV) trajectory tracking tasks, deep reinforcement learning controllers are applied to these conditions. These control problems are considered as a POMDP (Partially Observable Markov Decision Process). Model-free reinforcement learning(RL) algorithms for continuous control mission based on Deterministic Policy Gradient(DPG) allows robots learn from received delayed rewards when interacting with environments. Recurrent neural networks LSTM (Long Short-Term Memory) are involved into the reinforcement learning algorithm. Through this deep reinforcement learning algorithm, AUVs learn from sequences of dynamic information. The horizontal trajectory tracking tasks are described by LOS method and the motion control are idealized as a SISO model. Tanh-estimators are presented as data normalization. Moreover, AUV horizontal trajectory tracking and motion control simulation results demonstrate this algorithm gets better accuracy compared with the PID method and other non-recurrent methods. Efforts show the efficiency and effectiveness of the improved deep reinforcement learning algorithm.

关键词： Autonomous underwater vehicles

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Remote Sensing on a Bird-inspired Flapping Wings Robot Combined with LiDAR 3

Remote Sensing on a Bird-inspired Flapping Wings Robot Combi...

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3rd international conference on robotics, Automation and Intelligent control, ICRAIC 2023

作者： Wu, Lican Han, Yaqi Zhu, Qingyang Hao, Yi Ye, Ziming Huang, Ruqi Cai, Yu Fu, H.Y. Tsinghua University Shenzhen International Graduate School Guangdong Shenzhen China Guangxi University Nanning School of Electrical Engineering Guangxi China

ISBN: (纸本)9798350360813

The flapping wing robot (FWR), inspired by avian aerodynamics, is a distinct category of unmanned aerial vehicles (UAVs). Different to general UAVs, such as quadcopters, FWRs are featured by their superior aerodynamic capabilities, minimal noise generation, inherent stealth, and lower energy consumption. As a result, they are rapidly becoming vital tools in a variety of civilian and military activities including environmental monitoring, disaster detection, search and rescue operations, ecological conservation, and military manoeuvres. Our study introduces the comprehensive integration of a light detection and ranging (LiDAR) module, serving as a visual perception device, with a large FWR that is equipped with 2-meter, two-segment wings. Based on this setup, the geospatial information of targeted area is captured and compared to the existed topographic data. © 2023 IEEE.

关键词： Remote sensing

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Leukocyte segmentation and counting based on microscopic blood images using HSV saturation component with blob analysis 3

Leukocyte segmentation and counting based on microscopic blo...

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3rd international conference on control and robotics engineering, ICCRE 2018

作者： Quiñones, Vonn Vincent Macawile, Merl James Ballado, Alejandro Cruz, Jennifer Dela Caya, Meo Vincent School of Electrical Electronics and Computer Engineering Mapua University Manila Philippines

ISBN: (纸本)9781538666630

Determining the accurate count of leukocytes commonly known as WBC (white blood cells) in a blood test is critical in evaluating and diagnosing an individual's health particularly on a wide range of diseases which includes infections, anemia, leukemia etc. There are two widely used methods to determine leukocyte count. First, is through the use of hematology analyzer and the other is done manually. Nowadays, with the advent of technology leukocyte counting was improved through the use of digital image processing. However, the algorithm of the existing methods involves too many steps which complicates the image processing phase. Thus, we considered counting leukocytes by incorporating the HSV (Hue, Saturation, Value) saturation component with blob analysis on microscopic blood images which highlights the eccentricity and area features for counting to simplify existing methodologies which in turn generates faster and more accurate results. © 2018 IEEE.

关键词： Diagnosis

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