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arXiv 2024年

作者： Aucone, Emanuele Sferrazza, Carmelo Gregor, Manuel D'Andrea, Raffaello Mintchev, Stefano The Environmental Robotics Laboratory Dept. of Environmental Systems Science ETH Zürich Zürich8092 Switzerland Birmensdorf8903 Switzerland The Robot Learning Lab UC Berkeley BerkeleyCA94704 United States The Institute for Dynamic Systems and Control Dept. of Mechanical and Process Engineering ETH Zürich Zürich8092 Switzerland

Distributed tactile sensing for multi-force detection is crucial for various aerial robot interaction tasks. However, current contact sensing solutions on drones only exploit single end-effector sensors and cannot provide distributed multi-contact sensing. Designed to be easily mounted at the bottom of a drone, we propose an optical tactile sensor that features a large and curved soft sensing surface, a hollow structure and a new illumination system. Even when spaced only 2 cm apart, multiple contacts can be detected simultaneously using our software pipeline, which provides real-world quantities of 3D contact locations (mm) and 3D force vectors (N), with an accuracy of 1.5 mm and 0.17 N respectively. We demonstrate the sensor’s applicability and reliability onboard and in real-time with two demos related to i) the estimation of the compliance of different perches and subsequent re-alignment and landing on the stiffer one, and ii) the mapping of sparse obstacles. The implementation of our distributed tactile sensor represents a significant step towards attaining the full potential of drones as versatile robots capable of interacting with and navigating within complex environments. Copyright © 2024, The Authors. All rights reserved.

关键词： Drones

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Research on Target Detection Method Based on Improved YOLOv5 19th

Research on Target Detection Method Based on Improved YOLOv5

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19th International Conference on Web Information Systems and Applications, WISA 2022

作者： Wang, Rongzhuang Liu, Jun Zhang, Hualiang School of Computer Science and Technology Shenyang University of Chemical Technology Shenyang110142 China Liaoning Key Laboratory of Intelligent Technology for Chemical Process Industry Shenyang110142 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9783031203084

At present, various target detection algorithms are used in detection and classification. It is a problem to improve the accuracy and speed of target detection by using deep learning and neural network model to train the parameters of the data set. Aiming at the problems of insufficient detection, inaccurate detection of complex background and loss of small target feature information in yolov5 target detection, an improved method combining hole convolution, moving exponential average and retraining of positive samples is proposed in this paper. This method effectively solves the problems of complex background, occlusion and incomplete feature extraction, reduces the loss rate of target features, and improves the detection accuracy of each category. The improved yolov5 target detection algorithm in this paper can not only use multi feature fusion and accelerate positive sample matching, but also use cavity convolution to increase receptive field, improve the detection effect of small targets and reduce the occurrence of missed detection and false detection. Experiments show that the improved yolov5 algorithm has better detection rate and lower loss rate than many existing target detection algorithms. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Convolution

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Automatic generation of realistic training data for learning parallel-jaw grasping from synthetic stereo images

Automatic generation of realistic training data for learning...

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International Conference on Advanced robotics (ICAR)

作者： Justus Drögemüller Carlos X. Garcia Elena Gambaro Michael Suppa Jochen Steil Máximo A. Roa Technical University of Braunschweig Institute of Robotics and Process Control Technical University of Munich (TUM) Chair of Robotics Artificial Intelligence and Real-time Systems Roboception GmbH German Aerospace Center (DLR)

ISBN: (纸本)9781665436854

This paper proposes a novel approach to automatically generate labeled training data for predicting parallel-jaw grasps from stereo-matched depth images. We generate realistic depth images using Semi-Global Matching to compute disparity maps from synthetic data, which allows producing images that mimic the typical artifacts from real stereo matching in our data, thus reducing the gap from simulation to real execution. Our pipeline automatically generates grasp annotations for single or multiple objects on the synthetically rendered scenes, avoiding any manual image pre-processing steps such as inpainting or denoising. The labeled data is then used to train a CNN-model that predicts parallel-jaw grasps, even in scenarios with large amount of unknown depth values. We further show that scene properties such as the presence of obstacles (a bin, for instance) can be added to our pipeline, and the training process results in grasp prediction success rates of up to 90%.

关键词： Training Annotations Computational modeling Pipelines Noise reduction Training data Manuals

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Finite-time asynchronous dissipative filtering of conic-type nonlinear Markov jump systems

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Science China(Information Sciences) 2021年第5期64卷 151-162页

作者： Xiang ZHANG Shuping HE Vladimir STOJANOVIC Xiaoli LUAN Fei LIU Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) School of Electrical Engineering and Automation Anhui University Department of Automatic Control Robotics and Fluid Technique Faculty of Mechanical and Civil EngineeringUniversity of Kragujevac Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of AutomationJiangnan University

In the present study, the finite-time asynchronous dissipative filter design problem for the Markov jump systems with conic-type nonlinearity is studied. The hidden Markov model can describe the asynchronism embodied in the system modes and the filter modes reasonably. Moreover, a suitable LyapunovKrasovskii function is utilized and linear matrix inequalities are applied to obtain adequate conditions. These techniques guarantee the finite-time boundedness and strict dissipativity of the filtering error dynamic system. Furthermore, the design problems of the passive filter and the H∞ filter are studied by adjusting the three parameters U, G and V. Finally, the filter gains and the optimal index α*are obtained and the correctness and feasibility of the designed approach are verified by a simulation example.

关键词： dissipative filtering hidden Markov model finite-time boundedness Markov jump systems conic-type nonlinearity

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Distributed Optimization by Network Flows with Spatio-Temporal Compression

arXiv

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arXiv 2024年

作者： Ren, Zihao Wang, Lei Yi, Xinlei Wang, Xi Yuan, Deming Yang, Tao Wu, Zhengguang Shi, Guodong State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China College of Electronics and Information Engineering Tongji University China School of Electrical Engineering Telecommunications University of New South Wales Sydney Australia School of Automation Nanjing University of Science and Technology China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University China Australian Centre for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney SydneyNSW2006 Australia

Several data compressors have been proposed in distributed optimization frameworks of network systems to reduce communication overhead in large-scale applications. In this paper, we demonstrate that effective information compression may occur over time or space during sequences of node communications in distributed algorithms, leading to the concept of spatio-temporal compressors. This abstraction classifies existing compressors as spatio-temporal compressors, with their effectiveness described by constructive stability criteria from nonlinear system theory. Subsequently, we apply these spatio-temporal compressors to standard continuous-time consensus flows and distributed prime-dual flows, establishing conditions ensuring convergence. Additionally, we introduce a novel observer-based distributed primal-dual continuous flow integrated with spatio-temporal compressors, which provides broader convergence conditions. These continuous flows achieve exponential convergence to the global optimum when the objective function is strongly convex and can be discretized using Euler approximations. Finally, numerical simulations illustrate the versatility of the proposed spatio-temporal compressors and verify the convergence of algorithms. Copyright © 2024, The Authors. All rights reserved.

关键词： Stability criteria

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A Novel E-Nose Chamber Design for VOCs Detection in Automobiles

A Novel E-Nose Chamber Design for VOCs Detection in Automobi...

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第三十九届中国控制会议

作者： Lu Cheng Yin-Bo Liu Qing-Hao Meng Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Process Measurement and ControlSchool of Electrical and Information EngineeringTianjin University

To detect parts per billion（ppb）-level volatile organic compounds（VOCs） in automobiles, a pre-concentrator is generally needed for electronic noses（e-noses）, which can enrich ppb-level concentration to parts per million（ppm） level. However, the current e-nose chamber structure could dilute the pre-concentrated gases and then the detection performance is reduced. To solve this problem, a novel chamber design was proposed in this paper. The core design idea was to reduce the space for the gas flow in the chamber, taking into account the shape and size of the gas sensors. Specially, for the pin-type gas sensors, a series of cylindrical structure design was adopted, and for the micro-electro-mechanical system（MEMS） patch-type sensors, the headspace was compressed. The results of computational fluid dynamics（CFD） based simulation showed that the concentration of pre-concentrated gases in the novel chamber was higher than that of the traditional chamber. The designed chambers were manufactured using polylactic acid（PLA） material by 3D printing. Experimental gases were prepared from polyurethane（PU） leather and polyvinyl chloride（PVC） leather to verify the performance of the chambers, and the results demonstrated that the proposed new e-nose chamber was superior to the traditional one in terms of the pre-concentration effect, repeatability and classification performance.

关键词： e-nose chamber pre-concentrator parts per billion（ppb） volatile organic compounds（VOCs） repeatability classification

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Monocular Visual SLAM based on VGG Feature Point Extraction

Monocular Visual SLAM based on VGG Feature Point Extraction

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第三十九届中国控制会议

作者： Xu-Yang Dai Qing-Hao Meng Wen-Jian Zheng Shao-Kai Zhu Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Process Measurement and ControlSchool of Electrical and Information Engineering Tianjin University

Significant progress has been made in the field of visual SLAM（Simultaneous Localization and Mapping）. However, the localization accuracy of visual SLAM can be significantly reduced in low-texture and illumination-changing environments. To solve these problems, an enhanced visual SLAM algorithm based on VGG（Visual Geometry Group） network was proposed in this paper. Firstly, the VGG network for feature point extraction was incorporated into the visual odometry（VO） to achieve robust camera pose estimation. Secondly, an automatic corner annotation method was adopted to set up the training database, which could reduce the workload of data annotation. Thirdly, to make the backend optimization more suitable for the VGG based VO, the BA（bundle adjustment） optimization process was improved. Experimental results showed that, the proposed visual SLAM method outperformed the mainstream ORB-SLAM（Oriented FAST and Rotated BRIEF SLAM） method, in terms of the number of effective feature points, the robustness of feature matching process to light changes, and the accuracy of robot pose estimation.

关键词： monocular visual SLAM feature point extraction convolutional neural network

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Indoor Layout Estimation by Fusing Monocular RGB Image Features Extracted with HRNet

Indoor Layout Estimation by Fusing Monocular RGB Image Featu...

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第三十九届中国控制会议

作者： Rong-Ze Huang Yin-Bo Liu Meh Jabeen Qing-Hao Meng Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Process Measurement and ControlSchool of Electrical and Information EngineeringTianjin University

Indoor layout estimation(ILE) is a challenging research that segments the natural indoor scene image into floor,walls and ceiling,and it has a wide range of application prospects in the fields such as scene understanding,reconstruction,robot positioning,and virtual *** ILE method by merging multiple feature s from a monocular red-green-blue(RGB) image was ***,the High-resolution networks(HRNet) was used to extract the features of indoor corner keypoints(CKs) and informative edges(IEs) in the form of ***,the extracted features were then selected through a room type(RT)classification ***,a feature fusion algorithm was proposed,which obtained the initial layout hypothe sis through CK features and then continuously optimized the layout hypothe sis with IE *** proposed ILE method was validated on the large scene understanding challenge(LSUN) dataset.

关键词： Indoor layout estimation Corner keypoint Informative edge Fusion algorithm High-resolution net

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UAV-based Odor Source Localization in Multi-Building Environments Using Simulated Annealing Algorithm

UAV-based Odor Source Localization in Multi-Building Environ...

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第三十九届中国控制会议

作者： Zi-Zhen Yang Tao Jing Qing-Hao Meng Institute of Robotics and Autonomous System Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin University

A single unmanned-aerial-vehicle(UAV) based odor source localization(OSL) method for outdoor multi-building environments was proposed. The simulated annealing(SA) algorithm was introduced in this problem in consideration of the difficulties of relatively large search space, turbulent airflow in the building environment, and local concentration extrema near the building walls. To avoid the effect of rotating UAV rotors on airflow, a tunable diode laser absorption spectroscopy(TDLAS) rather than the contact gas sensor was used to collect odor information remotely. Moreover, a three-mode(plume finding, tracking, and escaping local extremum) searching framework was designed in the SA-based OSL method to equip the UAV with abilities of traversing the searching area and escaping local extrema rapidly. Simulation results on a robot active olfaction simulator show that, the UAV could effectively escape the local extremum, track the plume and localize the odor source in the area of 30×30×10 m with an average time of about 119 steps and an average error of 1.56 m.

关键词： Odor source localization active olfaction UAV multi-building environments simulated annealing

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Odor Evaluation of Vehicle Interior Materials Based on Portable E-nose

Odor Evaluation of Vehicle Interior Materials Based on Porta...

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第三十九届中国控制会议

作者： Zhe-Hua Sun Ke-Xian Liu Xue-Han Xu Qing-Hao Meng Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin University

The evaluation of the odor emitted by the interior materials is of great significance to the air quality control in the vehicle. This paper focuses on the multi-label classification problem of the odor type(i.e. the type of material from which the odor is released) and the grade evaluation in the vehicle. Two multi-label classifiers based on binary relevance(BR) and classification chain(CC) were designed to distinguish odor types and grades simultaneously and to distinguish odor types first and then grades, respectively. Based on the self-designed portable E-nose, six grades of odors released from six types of common interior materials were detected and classified. Experimental results showed that both the multi-label classifiers achieved better recognition accuracy, but the CC had an average recognition rate of 88.17% slightly better than the BR. It is preliminarily verified that the portable E-nose based multi-label classifiers could be used to evaluate the odor of automotive interior materials.

关键词： E-nose vehicle interior materials multi-label classifier Odor evaluation

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