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检索条件"任意字段=18th International Conference on Control Automation Robotics and Vision"

共 5313 条记录，以下是1161-1170 订阅

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Towards Semantic Scene Segmentation for Autonomous Agricultural Vehicles

Towards Semantic Scene Segmentation for Autonomous Agricultu...

引用

international conference on control, automation, robotics and vision (ICARCV)

作者： Esma Mujkic Dan Hermann Ole Ravn Morten L. Bilde Nils A. Andersen AGCO A/S Research and Advanced Engineering Randers Denmark Automation and Control Group Technical University Denmark Kgs. Lyngby Denmark

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

the development of autonomous agricultural vehicles depends on accurate visual interpretation of the environment. Semantic pixel-wise segmentation plays an important role in achieving a more detailed description of the scene and understanding of the spatial-relationship between different objects. In this paper, a deep architecture for road scene and indoor scene segmentation, SegNet, is applied in solving the scene recognition problem for the agricultural environment. the network is trained on an agriculture image dataset collected during field operation. the problem focuses on the segmentation of five classes of structures commonly found in the fields: vegetation, grass, ground, crop field and obstacles. We apply frequency balancing to address the challenge of class imbalance and transfer learning technique. the quantitative performance of the network is evaluated using pixel accuracy and intersection over union metrics. Moreover, we present an approach for an infield qualitative validation of the trained network.

关键词： Image segmentation Agriculture Computer architecture Training Semantics Decoding Task analysis

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Real-Time Queue Length Estimation With Trajectory Reconstruction Using Surveillance Data

Real-Time Queue Length Estimation With Trajectory Reconstruc...

引用

international conference on control, automation, robotics and vision (ICARCV)

作者： Zihao Sheng Shibei Xue Yunwen Xu Dewei Li Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

this paper presents a new method to estimate real-time queue lengths at a signalized intersection by utilizing limited data extracted from surveillance videos. this method focuses on reconstructing vehicles' trajectories on an entire road segment. the real-time queue length can be derived from these reconstructed trajectories. In order to improve the accuracy of the trajectory reconstruction, a built-up car-following model is proposed to reconstruct the trajectories of vehicles joining and leaving the queue, respectively, which are further corrected by a fusion algorithm. the proposed method was validated in the Next Generation Simulation dataset, and the queue length for each signal cycle can be estimated with a high accuracy. the results show that the proposed method has a higher precision compared to three baseline models.

关键词： Trajectory Surveillance Videos Real-time systems Image reconstruction Cameras Roads

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Consensus Kalman Filtering for Sensor Networks Based on FDI Attack Detection

Consensus Kalman Filtering for Sensor Networks Based on FDI ...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Jiali Hao Ya Zhang School of Automation Southeast University and with Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

this paper studies the consensus Kalman filtering algorithm with distributed attack detection for reducing the effects of false data injection attacks in wireless sensor networks. the FDI attacks are randomly injected into communication channels or sensors with certain probabilities, which undermines the accuracy of the transmission data and the accuracy of measurement data respectively. χ 2 detector is applied, and if the received data is determined to be attacked, it is omitted in consensus Kalman filtering. It is proved that if the FDI attack is randomly injected into communication channels, under the consensus Kalman filtering algorithm with adaptive weighting protocol and attack detection, the estimation errors of the sensor network can be bounded in probability. If the FDI attack is randomly injected into sensors, a probability condition on the attacks is given to guarantee the estimation errors of the sensor network bounded in mean square sense. Numerical simulations are conducted to demonstrate the performance of the proposed algorithms.

关键词： Covariance matrices Kalman filters State estimation Wireless sensor networks Robot sensing systems Distributed databases Detectors

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Laser Scanner Position Measurement Method and Accuracy Verification Based on Monocular vision 9

Laser Scanner Position Measurement Method and Accuracy Verif...

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9th IEEE Annual international conference on Cyber Technology in automation, control, and Intelligent Systems (IEEE-CYBER)

作者： Zhang, Jianhui Miao, Dongjing Chen, Zhiliang Wang, Guolei Tsinghua Univ Dept Mech Engn State Key Lab Tribol Beijing 100084 Peoples R China Natl Inst Metrol China Room 2022Bldg 518 North Third Ring Rd East Beijing 100029 Peoples R China

ISBN: (纸本)9781728107707

the method of position measurement based on monocular vision has a wide range of applications in various fields. In this paper, a method based on monocular vision for laser scanner position measurement is proposed and implemented. It can he applied to the three-dimensional reconstruction of point cloud by combining visual positioning technology with laser scanner. Firstly, this paper studies and designs a 3D target (the 3D target is mounted on the laser scanner) made by using the infrared LED light-emitting diode as the control points. then use the EPnP solution to solve the position of the laser scanner, including spatial position coordinates (x, y, z) and three Euler rotation angles (alpha, beta, gamma). the measurement method proposed in this paper is simple and easy to operate, and the experimental results show high measurement accuracy.

关键词： Scanning

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Comparison of camera-based and 3D LiDAR-based place recognition across weather conditions

Comparison of camera-based and 3D LiDAR-based place recognit...

引用

international conference on control, automation, robotics and vision (ICARCV)

作者： Kamil Żywanowski Adam Banaszczyk Michał R. Nowicki Institute of Robotics and Machine Intelligence Faculty of Control Robotics and Electrical Engineering Poznan University of Technology Poznan Poland

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

Place recognition based on camera images provides excellent results on benchmarking datasets but might struggle in real-world adverse weather conditions like direct sun, rain, fog, or just darkness at night. In automotive applications, the sensory setups include 3D LiDARs that provide information complementary to cameras. the presented article focuses on the evaluation of camera-based, LiDAR-based, and joint camera-LiDAR-based place recognition. the processing for all data inputs is performed using a similar architecture of a neural network and is evaluated under varying weather conditions using the newly available USyd dataset. the experiments performed on the same trajectories in diverse weather conditions over 50 weeks prove that a 16-line 3D LiDAR can be used to supplement image-based place recognition to increase its performance. this proves that there is a need for more research into place recognition performed with multi-sensory setups.

关键词： Laser radar three-dimensional displays Cameras Meteorology Training Pipelines Image recognition

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Model Predictive Path Integral control Framework for Partially Observable Navigation: A Quadrotor Case Study

Model Predictive Path Integral Control Framework for Partial...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Ihab S. Mohamed Guillaume Allibert Philippe Martinet Université Côte d’Azur Inria France Université Côte d’Azur CNRS I3S France

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

Recently, Model Predictive Path Integral (MPPI) control algorithm has been extensively applied to autonomous navigation tasks, where the cost map is mostly assumed to be known and the 2D navigation tasks are only performed. In this paper, we propose a generic MPPI control framework that can be used for 2D or 3D autonomous navigation tasks in either fully or partially observable environments, which are the most prevalent in robotics applications. this framework exploits directly the 3D-voxel grid acquired from an on-board sensing system for performing collision-free navigation. We test the framework, in realistic RotorS-based simulation, on goal-oriented quadrotor navigation tasks in a cluttered environment, for both fully and partially observable scenarios. Preliminary results demonstrate that the proposed framework works perfectly, under partial observability, in 2D and 3D cluttered environments.

关键词： Navigation Rotors Vehicle dynamics Task analysis Trajectory Two dimensional displays Real-time systems

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10th international conference on robotics, vision, Signal Processing and Power Applications 1

引用

丛书名： Lecture Notes in Electrical Engineering

2019年

作者： Mohamad Adzhar Md Zawawi Soo Siang Teoh Noramalina Binti Abdullah Mohd Ilyas Sobirin Mohd Sazali

ISBN: (数字)9789811364471

ISBN: (纸本)9789811364464;9789811364495

this proceedings book presents a collection of research papers from the 10th international conference on robotics, vision, Signal Processing & Power Applications (ROVISP 2018), which serves as a platform for researchers, scientists, engineers, academics and industrial professionals from around the globe to share their research findings and development activities. the book covers various topics of interest, including, but not limited to:;•Devices, Circuits and Embedded Systems

关键词： control, robotics, automation Artificial Intelligence Signal, Speech and Image Processing Electrical Power Engineering

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Swarm robotics Pattern Formation Algorithms

Swarm Robotics Pattern Formation Algorithms

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international conference on control, Mechatronics and automation (ICCMA)

作者： Mohamed H. Wagdy Hady A. Khalil Shady A. Maged Ain shams University Cairo Egypt

ISBN: (数字)9781728192109

ISBN: (纸本)9781728192116

Pattern formation is an important challenge in autonomous swarm robotics, it can drastically increase the efficiency of a group of robots and can be used in applications such as exploration and area coverage. Many pattern formation algorithms have been suggested with different constraints and assumptions of the robot's capabilities typically leaning towards robots with limited sensors meanwhile the proposed work relies on the current advancements in autonomous robots algorithms using robots with a wide range of sensors to tackle the pattern formation *** will present four main algorithms to solve the pattern formation problem mainly: peer detection, leader selection, pattern formation, and narrow path *** algorithms will be explained in this paper and are tested using ROS/Gazebo under different scenarios.

关键词： Robots Pattern formation Navigation Swarm robotics Sensors Robot vision systems Cameras

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Proceedings - 2019 4th international conference on automation, control and robotics Engineering, CACRE 2019

Proceedings - 2019 4th International Conference on Automatio...

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4th international conference on automation, control and robotics Engineering, CACRE 2019

ISBN: (纸本)9781450371865

the proceedings contain 75 papers. the topics discussed include: assembly defect detection of atomizers based on machine vision;research on lithium-ion batteries state of charge estimation based on interactive multiple-model cubature filter;research on modern design technology of the recuperator combined with neural network;research on adhesive workpiece recognition and positioning based on machine vision;design and test of multi-information storage testing system in complex physical environment;design of a multi-channel and multi-parameter fuze test system;surface multi-target tracking algorithm based on data association of information fusion;surface multi-target tracking algorithm based on data association of information fusion;and research on error modeling and compensation method of hot rolling shape setting model based on cluster and neural network.

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Relative degree one and two sliding variables for multi-input discrete-time systems 24

Relative degree one and two sliding variables for multi-inpu...

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24th international conference on Methods and Models in automation and robotics (MMAR)

作者： Latosinski, Pawel Bartoszewicz, Andrzej Lodz Univ Technol Inst Automat Control 18-22 B Stefanowskiego St PL-90924 Lodz Poland

ISBN: (纸本)9781728109336

In this paper we consider sliding mode control of multi-input discrete-time plants. For such plants, we propose the use of relative degree two sliding variables, which are known to improve robustness of single-input plants compared to their relative degree one equivalent. We investigate the design procedure of relative degree two sliding variables for multi-input systems. then, we present two sliding mode control strategies obtained with the reaching law approach, using relative degree one and two sliding variables, respectively. We demonstrate that both reaching laws ensure desirable properties of the system sliding motion and that the method using relative degree two sliding variables ensures better robustness of the system than the one with relative degree one variables. We further show that the proposed reaching law based strategies enable independent tuning of individual inputs.

关键词： Sliding mode control Uncertainty Robustness Switches Discrete-time systems Process control

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