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Accurate RGB-D SLAM in dynamic environments based on dynamic visual feature removal

Science China(Information Sciences) 2022年第10期65卷 256-269页

作者： Chenxin LIU Jiahu QIN Shuai WANG Lei YU Yaonan WANG Department of Automation University of Science and Technology of China Institute of Artificial Intelligence Hefei Comprehensive National Science Center College of Electrical and Information Engineering Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University

visual localization is considered an essential capability in robotics and has attracted increasing interest for the past few years. However, most proposed visual localization systems assume that the surrounding environment is static, which is difficult to maintain in real-world scenarios due to the presence of moving objects. In this paper, we present DFR-SLAM, a real-time and accurate RGB-D SLAM based on ORB-SLAM2 that achieves satisfactory performance in a variety of challenging dynamic scenarios. At the core of our system lies a motion consensus filtering algorithm estimating the initial camera pose and a graph-cut optimization framework combining long-term observations, prior information, and spatial coherence to jointly distinguish dynamic and static visual features. Other systems for dynamic environments detect dynamic components by using the information from short time-span frames, whereas our system uses observations from a long period of keyframes. We evaluate our system using dynamic sequences from the public TUM dataset, and the evaluation demonstrates that the proposed system outperforms the original ORB-SLAM2 system significantly. In addition, our system provides competitive localization accuracy with satisfactory real-time performance compared to closely related SLAM systems designed to adapt to dynamic environments.

关键词： SLAM dynamic environments indoor localization graph-cut robot navigation

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An intelligent route recommendation method for smart Internet-connected electric vehicles under the coupling of traffic and electricity

An intelligent route recommendation method for smart Interne...

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第42届中国控制会议

作者： JinhuanXie Dongqi Liu ZhenwuYang School of Electrical and Information Engineering Changsha University of Science and Technology National Engineering Research Center for Robot Visual Perception and Control Technology

Aiming at the charging and navigation strategy of electric vehicles in the road-electricity coupling scenario,this paper proposes a hybrid planning travel scheme based on the pre-charging and charging warning model based on the road traffic congestion predicted by the big data of the Internet of *** model integrally balances the interests of users and power grid in the coupled road-electric network,and solves the optimal path scheme under different travel scenarios based on collaborative filtering algorithm and user feedback,considering the influence of vehicle departure time and remaining power in short time *** is experimentally demonstrated that the proposed route hybrid recommendation model has better planning effect compared with the single travel model.

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Towards Consistent Object Detection via LiDAR-Camera Synergy

Towards Consistent Object Detection via LiDAR-Camera Synergy

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Luo, Kai Wu, Hao Yi, Kefu Yang, Kailun Hao, Wei Hu, Rongdong College of Automotive and Mechanical Engineering Changsha University of Science and Technology China School of Traffic and Transportation Engineering Changsha University of Science and Technology China School of Robotics Hunan University China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University China Changsha Intelligent Driving Institute China

ISBN: (纸本)9781665410205

As human-machine interaction continues to evolve, the capacity for environmental perception is becoming increasingly crucial. Integrating the two most common types of sensory data, images, and point clouds, can enhance detection accuracy. Currently, there is no existing model capable of detecting an object's position in both point clouds and images while also determining their corresponding relationship. This information is invaluable for human-machine interactions, offering new possibilities for their enhancement. In light of this, this paper introduces an end-to-end Consistency Object Detection (COD) algorithm framework that requires only a single forward inference to simultaneously obtain an object's position in both point clouds and images and establish their correlation. Furthermore, to assess the accuracy of the object correlation between point clouds and images, this paper proposes a new evaluation metric, Consistency Precision (CP). To verify the effectiveness of the proposed framework, an extensive set of experiments has been conducted on the KITTI and DAIR-V2X datasets. The study also explored how the proposed consistency detection method performs on images when the calibration parameters between images and point clouds are disturbed, compared to existing post-processing methods. The experimental results demonstrate that the proposed method exhibits ex-cellent detection performance and robustness, achieving end-to-end consistency detection. The source code will be made publicly available at https://***/xifen523/COD. © 2024 IEEE.

关键词： Object detection

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Design and Analysis of a Synergy-Inspired Three-Fingered Hand

Design and Analysis of a Synergy-Inspired Three-Fingered Han...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Wenrui Chen Zhilan Xiao Jingwen Lu Zilong Zhao Yaonan Wang National Engineering Laboratory for Robot Vision Perception and Control Technology Hunan University Changsha China

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Hand synergy from neuroscience provides an effective tool for anthropomorphic hands to realize versatile grasping with simple planning and control. This paper aims to extend the synergy-inspired design from anthropomorphic hands to multi-fingered robot hands. The synergy-inspired hands are not necessarily humanoid in morphology but perform primary characteristics and functions similar to the human hand. At first, the biomechanics of hand synergy is investigated. Three biomechanical characteristics of the human hand synergy are explored as a basis for the mechanical simplification of the robot hands. Secondly, according to the synergy characteristics, a three-fingered hand is designed, and its kinematic model is developed for the analysis of some typical grasping and manipulation functions. Finally, a prototype is developed and preliminary grasping experiments validate the effectiveness of the design and analysis.

关键词： Thumb robots Joints Muscles Grasping Electronics packaging

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A Muti-stage Selection Filter Based on Wavelet Packet and 2DCNN for Fault Diagnosis of Rotating Machinery 42

A Muti-stage Selection Filter Based on Wavelet Packet and 2D...

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42nd Chinese control Conference, CCC 2023

作者： He, Wenbin Mao, Jianxu Liu, Li Li, Zhe Yang, Miao Wang, Yaonan College of Electrical and Information Engineering Hunan University Changsha410082 China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China State Grid Hunan Electric Power Company Limited Research Institute Changsha410007 China

ISBN: (纸本)9789887581543

Fault information of rotating machinery is often drowned in strong noise signals, so it is crucial to accurately identify faults from high-intensity noise signals. In this article, an end-to-end fault diagnosis model is developed, which consists of a multi-stage selection filter based on wavelet packet and 2D-CNN. First, the original measured mechanical signals were processed by the three-level wavelet packet decomposition to obtain eight sub-bands with coefficient matrices. Second, the signal is reconstructed using different numbers of sub-bands, where the number is increased by one at a time to obtain eight different multi-stage reconstructed signals. Third, the reconstructed signals are reorganized into 2D signal maps;and a parallel training network is constructed using signal maps and 2D-CNN to achieve fault classification. Then, guided by the training results, eight parallel classification results are compared, so as to train the best fault diagnosis model. Finally, the simulation experiment based on a bearing data set illustrates the proposed multi-stage selection filter is effective and feasible in application. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Failure analysis

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P2U-SLAM: A Monocular Wide-FoV SLAM System Based on Point Uncertainty and Pose Uncertainty

arXiv

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arXiv 2024年

作者： Zhang, Yufan Yang, Kailun Wang, Ze Wang, Kaiwei The State Key Laboratory of Extreme Photonics and Instrumentation Zhejiang University Hangzhou310027 China The School of Robotics The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410012 China The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China

This paper presents P2U-SLAM, a visual Simultaneous Localization And Mapping (SLAM) system with a wide Field of View (FoV) camera, which utilizes pose uncertainty and point uncertainty. While the wide FoV enables considerable repetitive observations of historical map points for matching cross-view features, the data properties of the historical map points and the poses of historical keyframes have changed during the optimization process. The neglect of data property changes triggers the absence of a partial information matrix in optimization and leads to the risk of long-term positioning performance degradation. The purpose of our research is to reduce the risk of the wide field of view visual input to the SLAM system. Based on the conditional probability model, this work reveals the definite impact of the above data properties changes on the optimization process, concretizes it as point uncertainty and pose uncertainty, and gives a specific mathematical form. P2U-SLAM respectively embeds point uncertainty and pose uncertainty into the tracking module and local mapping, and updates these uncertainties after each optimization operation including local mapping, map merging, and loop closing. We present an exhaustive evaluation in 27 sequences from two popular public datasets with wide-FoV visual input. P2U-SLAM shows excellent performance compared with other state-of-the-art methods. The source code will be made publicly available at https://***/BambValley/P2U-SLAM. Copyright © 2024, The Authors. All rights reserved.

关键词： Mapping

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Motion Planning for Mobile robots with Temporal Logic Specifications

Motion Planning for Mobile Robots with Temporal Logic Specif...

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Jianxin Zeng Yaonan Wang Zhiqiang Miao Sifei Wang College of Electrical and Information Engineering and the National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha China

In this paper, we propose a motion planning method for mobile robots in order to satisfy task requirements specified in linear temporal logic (LTL). The proposed method follows the traditional hierarchical planning workflow, including path planning and trajectory planning. Firstly, we propose a path planning method based on rapidly exploring random trees (RRT*) and Dubins curve. The tree derived from RRT* is expanded with the help of Buchi automaton converted by an LTL formula. The proposed method can automatically adjust the iterations of sampling according to the scale of Buchi automata. Then, we formulate an optimization problem for the generation of trajectory. We use Bezier curve to express the trajectory and use differential flatness of mobile robots to simplify the optimization problem. Finally, we validate the practicality of our method through simulations and real-world experiments.

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PL-VINS: Real-Time Monocular visual-Inertial SLAM with Point and Line Features

arXiv

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arXiv 2020年

作者： Fu, Qiang Wang, Jialong Yu, Hongshan Ali, Islam Guo, Feng He, Yijia Zhang, Hong National Engineering Laboratory for Robot Visual Perception and Control Technology Hunan University China Department of Computing Science University of Alberta Canada Megvii Technology Beijing China

Leveraging line features to improve localization accuracy of point-based visual-inertial SLAM (VINS) is gaining interest as they provide additional constraints on scene structure. However, real-time performance when incorporating line features in VINS has not been addressed. This paper presents PL-VINS, a real-time and high-efficiency optimization-based monocular VINS method with point and line features, developed based on the state-of-the-art point-based VINS-Mono [1]. We observe that current works use the LSD [2] algorithm to extract line features;however, LSD is designed for scene shape representation instead of the pose estimation problem, which becomes the bottleneck for the real-time performance due to its high computational cost. In this paper, we modify the LSD algorithm by studying a hidden parameter tuning and length rejection strategy. The modified LSD algorithm can run at least three times as fast as LSD. Further, by representing space lines with the Plücker coordinates, the residual error in line estimation is modeled in terms of the point-to-line distance, which is then minimized by iteratively updating the minimum four-parameter orthonormal representation of the Plücker coordinates. Experiments in a public benchmark dataset show that the localization error of our method is 12-16% less than that of VINS-Mono at the same pose update frequency. The source code of our method is available at: https://***/cnqiangfu/PL-VINS. Copyright © 2020, The Authors. All rights reserved.

关键词： Iterative methods

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Multi-Expert Adversarial Attack Detection in Person Re-identification Using Context Inconsistency

arXiv

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arXiv 2021年

作者： Wang, Xueping Li, Shasha Liu, Min Wang, Yaonan Roy-Chowdhury, Amit K. College of Electrical and Information Engineering Hunan University China National Engineering Laboratory for Robot Visual Perception and Control Technology China University of California Riverside United States

The success of deep neural networks (DNNs) has promoted the widespread applications of person reidentification (ReID). However, ReID systems inherit the vulnerability of DNNs to malicious attacks of visually inconspicuous adversarial perturbations. Detection of adversarial attacks is, therefore, a fundamental requirement for robust ReID systems. In this work, we propose a Multi-Expert Adversarial Attack Detection (MEAAD) approach to achieve this goal by checking context inconsistency, which is suitable for any DNN-based ReID systems. Specifically, three kinds of context inconsistencies caused by adversarial attacks are employed to learn a detector for distinguishing the perturbed examples, i.e., a) the embedding distances between a perturbed query person image and its top-K retrievals are generally larger than those between a benign query image and its top-K retrievals, b) the embedding distances among the top-K retrievals of a perturbed query image are larger than those of a benign query image, c) the top-K retrievals of a benign query image obtained with multiple expert ReID models tend to be consistent, which is not preserved when attacks are present. Extensive experiments on the Market1501 and DukeMTMC-ReID datasets show that, as the first adversarial attack detection approach for ReID, MEAAD effectively detects various adversarial attacks and achieves high ROC-AUC (over 97.5%). Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

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Formation control with Connectivity Maintenance for Double-Integrator Multi-Agent Systems

Formation Control with Connectivity Maintenance for Double-I...

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第三十八届中国控制会议

作者： Zhiqiang Miao Yaonan Wang College of Electrical and Information Engineering Hunan University Shenzhen Research Institute of Hunan University National Engineering Laboratory for Robot Visual Perception and Control

The network connectivity maintenance problem in formation control of mobile agents with double-integrator dynamics is addressed in this paper. Distributed potential field-based controllers are proposed for double-integrator agent group to maintain the connectivity of communication graph until the desired formation is achieved. We also investigate the connectivity preserving formation control with a virtual leader. Providing that at least one agent has information about the leader, all agents can asymptotically reach the desired formation and attain the same velocity as the virtual leader. The asymptotic stability analysis is presented with Lyapunov-like tools including LaSalle's invariance principle and Barbalat's lemma. Simulation results on a group of agents with double-integrator dynamics are presented to demonstrate the effectiveness of the proposed strategies.

关键词： formation control multi-agent systems connectivity maintenance

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