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

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Vehicle Detection and Width Estimation in Rain by Fusing Radar and vision 15

Vehicle Detection and Width Estimation in Rain by Fusing Rad...

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15th international conference on control, automation, robotics and vision (ICARCV)

作者： Wang, Jian-Gang Chen, Simon Jian Zhou, Lu-Bing Wan, Kong-Wah Yau, Wei-Yun Inst Infocomm Res Robot Dept 1 Fusionopolis Way21-01 Connexis South Tower Singapore 138632 Singapore Desay SV Automot ICON IBP 3A Int Business Pk 09-13 Tower B Singapore 609935 Singapore Inst Infocomm Res Autonomous Vehicle Dept Singapore Singapore NuTonomy 77 Ayer Rajah Crescent Singapore 139954 Singapore

ISBN: (纸本)9781538695821

While much effort has been devoted to deep learning object detection, relatively limited attention has been paid to object detection in bad weather, e.g. rain, snow or haze. In heavy rain, the raindrop on the front windshield can make it difficult to detect object from an in-car camera. the conventional way to cope with this has been to use radar as the main detection sensor. However, radar is highly susceptible to false positives. Furthermore, many entry level radar sensors only return the centroid of each detected object, rather than its size and extent. In addition, due to lack of texture input, radar cannot discriminate a vehicle from a non-vehicle object, e.g. roadside pole. this motivates us to detect vehicle by fusing radar and vision. In this paper, we first calibrate the radar and camera with respect to the ground plane. the radar detections are then projected to the camera image for target width estimation. Empirical evaluation on a large database shows that there is a natural synergy in both sensors, as the image based estimation is found to be greatly facilitated by the accuracy of the radar detection.

关键词： Object detection

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Multi-robot motion-formation distributed control with sensor self-calibration: experimental validation. 15

Multi-robot motion-formation distributed control with sensor...

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15th international conference on control, automation, robotics and vision (ICARCV)

作者： de Marina, Hector Garcia Siemonsma, Johan Jayawardhana, Bayu Cao, Ming Southern Univ Denmark Maersk Mc Kinney Moller Inst Unmanned Aerial Syst Ctr Odense Denmark Univ Groningen Engn & Technol Inst Groningen Fac Sci & Engn Groningen Netherlands

ISBN: (纸本)9781538695821

In this paper, we present the design and implementation of a robust motion formation distributed control algorithm for a team of mobile robots. the primary task for the team is to form a geometric shape, which can be freely translated and rotated at the same time. this approach makes the robots to behave as a cohesive whole, which can be useful in tasks such as collaborative transportation. the robustness of the algorithm relies on the fact that each robot employs only local measurements from a laser sensor which does not need to be off-line calibrated. Furthermore, robots do not need to exchange any information with each other. Being free of sensor calibration and not requiring a communication channel helps the scaling of the overall system to a large number of robots. In addition, since the robots do not need any off-board localization system, but require only relative positions with respect to their neighbors, it can be aimed to have a full autonomous team that operates in environments where such localization systems are not available. the computational cost of the algorithm is inexpensive and the resources from a standard microcontroller will suffice. this fact makes the usage of our approach appealing as a support for other more demanding algorithms, e.g., processing images from onboard cameras. We validate the performance of the algorithm with a team of four mobile robots equipped with low-cost commercially available laser scanners.

关键词： Mobile robots

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the applicability of on-line contextual calibration to a neural network based monocular collision avoidance system on a UAV 5th

The applicability of on-line contextual calibration to a neu...

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5th IFAC conference on Intelligent control and automation Sciences (ICONS)

作者： Hiba, Antal Aleksziev, Rita Pazman, Koppany Bauer, Peter Benczur, Andras Zarandy, Akos Daroczy, Balint Hungarian Acad Sci Inst Comp Sci & Control Budapest Hungary Szechenyi Istvan Univ Res Ctr Vehicle Ind Gyor Hungary Pazmany Peter Catholic Univ Budapest Hungary

Contextual calibration for object detection is a technique where a pretrained network collects attractive false positives during a calibration phase and use this calibration data for further training. this paper investigates the applicability of this method to a vision based onboard sense and avoid system, which requires intruder aircraft detection in camera images. Various landscape and sky backgrounds were generated by Unreal4 3D engine for calibration tests. Contextual calibration is a promising candidate for handling extreme situations which are not covered well in the training data. (C) 2019, IFAC (international Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Learning adaptation and evaluation Aerospace robotics and autonomous systems

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Maximum Contrast Imaging Using Chromatic Lighting and Fuzzy Logic: Analyses of Old Handwritings 18

Maximum Contrast Imaging Using Chromatic Lighting and Fuzzy ...

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18th international conference on control, automation and Systems (ICCAS)

作者： Kim, Hyungtae Ki, Namkyeong Nam, Kyeongnan Nam, Kwon-Hee KITSCH Smart Mfg Technol Grp Cheonan 31056 Chungnam South Korea Deagu Catholic Univ Dept Korean Language & Literature Gyongsan 38430 Kyungpook South Korea Kyungpook Natl Univ Dept Lib & Informat Sci Daegu 41566 South Korea

ISBN: (纸本)9788993215151

Machine vision has been applied to many industrial areas. It has also become popular in heritage science. this study proposes maximum contrast imaging to determine the appropriate light color and intensity to increase the discriminating ability for image analyses. the contrast of an image was evaluated in accordance to various digital focus indices (DFIs), and their formulations were thus investigated. Optimal conditions of focus, light color, and intensity were determined based on the maxima of the DFIs. Fuzzy logic was applied to verify the determined owing to the different DFI maxima. the proposed method was implemented subject to the assumption of an arbitrary number of light colors. In the experiment, the DFIs were constructed using C/C++ libraries compatible with OpenCV and the decision methods were verified using an automated optical inspection (AOI) machine. Test targets were old handwritings in a xylograph book, and optimal conditions were determined in the case of a multi-color light source. the handwritings were initially illegible but became readable using maximum contrast images. this study showed that maximum contrast imaging will be useful in industrial applications, such as automatic optical inspection, and in the analyses of historical objects.

关键词： Image Contrast Digital Focus Index OpenCV Automatic Lighting Color control Machine vision Fuzzy Logic

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Water flow Detection Using Deep Convolutional Encoder-decoder Architecture 18

Water flow Detection Using Deep Convolutional Encoder-decode...

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18th international conference on control, automation and Systems (ICCAS)

作者： Baydargil, Husnu Baris Park, Jangsik Shin, Hyun-Suk Park, Kwanghee Kyungsung Univ Dept Elect & Elect Engn 309 Suyeong Ro Busan 48434 South Korea Pusan Natl Univ Dept Civil & Environm Engn Busan South Korea Busan Traff Informat Ctr Busan South Korea

ISBN: (纸本)9788993215151

Due to shortcomings in sewage systems, there are areas in many cities that are highly susceptible to flooding in heavy rain scenarios. While the CCTV cameras for variety reasons scattered everywhere around the city, detecting sudden developed situations still require human attention and focus. Especially in emergency disaster situations, necessary actions that need to be done should also he quick in order to minimize the impact. Detecting flooding early on can save human lives, time, money for the government, as well as an important step to move towards smarter cities. In this paper, the authors propose a deep learning approach to detect floods in certain susceptible areas due to numerous reasons. Using state-of-the-art architecture capable of image segmentation, the system is trained to detect floods using either CCTV or PTZ-capable cameras, and the alert center is warned about the flooded area in order to divert units to respond accordingly to the situation.

关键词： Scene understanding video automation computer vision image segmentation video surveillance flood detection deep learning emergency management

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Assessment of Upper Limb Tremors in Patients with Parkinson's Disease Based on Displacement and Acceleration Information

Assessment of Upper Limb Tremors in Patients with Parkinson'...

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

作者： Haoran Wu Yanan Zhang Xi Wu Fan Yang School of Mechatronic Engineering and Automation Shanghai University Changhai Hospital

ISBN: (数字)9781728198880

ISBN: (纸本)9781728198897

To examine the consistency between upper limb tremor scores for patients with Parkinson's disease(PD) obtained after comprehensively processing and modeling limb displacement and acceleration information and doctors' scores and to refine the scores. In this way, wearable devices can be used to assist doctors' treatment and improve their work efficiency. Seventeen PD patients wearing detection devices completed the standard movements stipulated in Part III of the Unified Parkinson's Disease Rating Scale for examining resting and postural tremors(RTs and PTs), during which the acceleration signals(ASs) of the patients' movements were collected. the AS and DS are denoised by using the designed wavelet automatic filtering process. A sliding window is used to select the most obvious period of tremor during detection. then extract the characteristic values from time domain, frequency domain and spectral domain respectively, and explore the most suitable model method for this study. In terms of reflecting the physical characteristics of tremors, the AS and DS eigenvalue sets each had their own advantages. For the RTs, there were stronger correlations between the AS eigenvalue set and doctors' scores. the average correlation coefficients(rs) of the AS and DS eigenvalue sets were 0.798(0.630–0.895, at the 95% confidence interval) and 0.731(0.522–0.857, at the 95% confidence interval), respectively. It was the opposite for the PTs, where the average rs of the AS and DS eigenvalue sets were 0.759(0.566–0.873, at the 95% confidence interval) and 0.845(0.709–0.920, at the 95% confidence interval), respectively. the results showed that compared to the support vector machine, random forest and multivariate linear regression models, the neural network model had higher accuracy(the accuracy for RT and PT scores were 0.953 and 0.912, respectively). Using a combination of ASs and DSs can effectively simulate doctors' scores for RTs and PTs in the upper limbs of PD patients.

关键词： parkinson's tremor quantitative scoring wearable device machine learning

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Implementation of the hybrid technology for quadcopter motion control in a complex non deterministic environment 18

Implementation of the hybrid technology for quadcopter motio...

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18th international conference on control, automation and Systems (ICCAS)

作者： Devitt, D. Morozov, R. Medvedev, M. Shapovalov, I Konovalov, G. Southern Fed Univ Res & Dev Inst Robot & Control Syst Taganrog 347900 Russia

ISBN: (纸本)9788993215151

this paper represents the results of development and research of the autonomous control system for the UAV. Existing control systems do not provide flight performance necessary for successful operations in non-deterministic environments. So, we propose hybrid intelligent technology based on unstable modes and the conception of a virtual goal. the main feature of our approach is the efficient integration of global and local path planning providing smooth and quick correction of trajectories for the avoidance of obstacles detected by the quadrotor vision system. Moreover, our local planning approach gives the tool for passing areas with complex obstacles where other local path planning algorithms fail, the hardware-software architecture of the control system based on client-server model with the loose coupling in ROS is presented. the results of simulation and real test flights confirming the efficiency of the proposed technology are shown. We used the commercially available quadcopter and flight controller. that proves absence of necessity in special hardware tools for autonomous flight in environments with uncertainties.

关键词： Motion control planning PID quadcopter unstable mode virtual goal 3D environment

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Performance Analysis and Dexterity Monitoring of Hexapod-Based Simulator 4

Performance Analysis and Dexterity Monitoring of Hexapod-Bas...

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4th international conference on control, automation and robotics (ICCAR)

作者： Qazani, Mohammad Reza Chalak Asadi, Houshyar Pedrammehr, Siamak Nahavandi, Saeid Deakin Univ IISRI Inst Intelligent Syst Res & Innovat Geelong Vic Australia

ISBN: (纸本)9781538663387

Washout filter is in demand to generate the vehicle acceleration and angular velocities with high loyalty to make the best realistic motion. the limitation of the simulator's moving platform is an integral part of every motion simulator. Adaptive and model predictive control washout filters contribute with this limitation online. It is necessary to have a real vision to the workspace limitation which is needed for unpredicted next step of the simulator. In this paper dexterity analysis is addressed as a novel method to monitor the performance accuracy of the simulator. the dexterity of both the classical and optimal washout filters are compared. Finally, it is shown that the dexterity analysis in optimal washout filter is necessary to avoid the workspace limitations.

关键词： parallel-based simulator dexterity analysis classical washout filter optimal washout filter

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Fuzzy-Model-Based Leader-Follower Consensus of Nonlinear Multi-Agent Systems with Input Saturation 15

Fuzzy-Model-Based Leader-Follower Consensus of Nonlinear Mul...

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15th international conference on control, automation, robotics and vision (ICARCV)

作者： Liu, Xiaolu Chen, Duxin Wang, Yan-Wu Yan, Huaicheng Huazhong Univ Sci & Technol Sch Automat Wuhan 430074 Hubei Peoples R China Southeast Univ Sch Math Nanjing 211189 Jiangsu Peoples R China East China Univ Sci & Technol Minist Educ Key Lab Adv Control & Optimizat Chem Proc Shanghai 200237 Peoples R China East China Univ Sci & Technol Sch Informat Sci & Engn Shanghai 200237 Peoples R China

ISBN: (纸本)9781538695821

this paper presents a fuzzy-model-based method for solving the consensus problem of a class of nonlinear multi-agent systems (MASs) with input saturation. Since each agent has nonlinear dynamics, the system is not asymptotically null controllable with bounded controls (ANCBC). therefore, the widely-used low-gain feedback method for designing consensus protocols of MASs with input saturation can no longer work. To this end, the Takagi-Sugeno (T-S) fuzzy model is adopted to formulate the error dynamics of those nonlinear follower agents with input saturation as well as a leader with time-varying states. Accordingly, by using the properties of convex hull, a set of invariance condition in the format of linear matrix inequality (LMI) is designed. Furthermore, by enlarging the shape reference set, the estimation of the attraction domain can be obtained. Simultaneously, by viewing the control gain as an extra free parameter in the LMI optimization procedure, the leader-follower consensus algorithm is proposed, which guarantees that all followers with input saturation can track the leader, and they can asymptotically reach consensus. Finally, numerical experiments validate the effectiveness of the proposed anti-saturation consensus algorithm.

关键词： Multi agent systems

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Sliding Window Bag-of-Visual-Words for Low Computational Power robotics Scene Matching 4

Sliding Window Bag-of-Visual-Words for Low Computational Pow...

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4th international conference on control, automation and robotics (ICCAR)

作者： Ginn, Daniel Mendes, Alexandre Chalup, Stephan Chen, Zhiyong Univ Newcastle Fac Engn & Built Environm Sch Elect Engn & Comp Newcastle NSW Australia

ISBN: (纸本)9781538663387

In this paper, we introduce a new method, based on a sliding window geometrical extension to Bag-of-Visual-Words (called swBOVW) intended for application to low computational power robots. Benchmarked against RANSAC as a geometric validator to BOVW, three implementations of this technique are presented to improve either the performance or the computational cost. the three implementations are: as a replacement to RANSAC as a geometric validator;as a supplement to RANSAC;and as a replacement to traditional BOVW when the number of images in the database can be reduced. Seeking to utilise some of the geometric information ignored by traditional BOVW, this technique is developed from the use of sub-regions in Spatial Pyramids, and applied to the matching of whole images. this technique is applied in the context of humanoid robotic soccer to the problem of field end symmetry, and provides geometric validation along the horizontal axis of images. When applied, the technique has been able to either halve the cases of unresolved image queries, or halve the computational cost required to achieve comparable results to the benchmark.

关键词： BOVW bag-of-visual-words image matching robotics machine vision

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