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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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Current Status,Challenges,and Prospects for New Types of Aerial robots

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engineering 2024年第10期41卷 19-34页

作者： Xidong Zhou Hang Zhong Hui Zhang Wei He Hean Hua Yaonan Wang College of Robotics Hunan UniversityChangsha 410082China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan UniversityChangsha 410082China School of Intelligence Science and Technology Beijing University of Science and TechnologyBeijing 100083China

New types of aerial robots(NTARs)have found extensive applications in the military,civilian contexts,scientific research,disaster management,and various other *** with traditional aerial robots,NTARs exhibit a broader range of morphological diversity,locomotion capabilities,and enhanced operational ***,this study defines aerial robots with the four characteristics of morphability,biomimicry,multi-modal locomotion,and manipulator attachment as ***,this paper discusses the latest research progress in the materials and manufacturing technology,actuation technology,and perception and control technology of ***,the research status of NTAR systems is summarized,focusing on the frontier development and application cases of flapping-wing microair vehicles,perching aerial robots,amphibious robots,and operational aerial ***,the main challenges presented by NTARs in terms of energy,materials,and perception are analyzed,and the future development trends of NTARs are summarized in terms of size and endurance,mechatronics,and complex scenarios,providing a reference direction for the follow-up exploration of NTARs.

关键词： Aerial robot Morphability Biomimicry Perch Amphibious

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Within-Hand Manipulation with an Underactuated Dexterous Hand Based on Pre-Trained Reinforcement Learning

Within-Hand Manipulation with an Underactuated Dexterous Han...

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Chinese Automation Congress (CAC)

作者： Xin Li Wenrui Chen Yaonan Wang Qiang Diao Sijie Wu Fan Yang National Engineering Research Center for Robot Visual Perception and Control College of Electrical and Information Engineering Hunan University Changsha China National Engineering Research Center for Robot Visual Perception and Control School of Robotics Hunan University Changsha China National Engineering Research Center for Robot Visual Perception and Control College of Mechanical and Vehicle Engineering Hunan University Changsha China

This paper investigates a dexterous manipulation method for multi-fingered hands based on the approximate policy optimization (PPO) algorithm. First, a prior knowledge base of dexterous manipulation demonstration data is provided for the PPO algorithm, and the original model is pre-trained to guide fast network training. Second, a new reward function is proposed to optimize rotational manipulation action decisions based on hand joints, fingertip tactile, and object pose infor mation. Finally, a three-fingered hand is used as an example for rotational manipulation experiments, and the comparative simulation results show that the method is more efficient than the traditional PPO algorithm and provides ideas for dexterous manipulation of multi-fingered hands.

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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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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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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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Steady Tracker: Tracking a Target Stably Using a Quadrotor

Steady Tracker: Tracking a Target Stably Using a Quadrotor

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Li, Hongwen Zhong, Hang Lv, Yongsheng Sha, Jianjun Long, Yu Wang, Yaonan Harbin Engineering University Harbin150001 China Qingdao Innovation and Development Center Harbin Engineering University Qingdao266000 China School of Robotics National Engineering Research Center for Robot Visual Perception and Control Hunan University China College of Electrical and Information Engineering Hunan University Changsha410082 China

ISBN: (纸本)9781665481090

Maneuvering target tracking of Unmanned Aerial Vehicle(UAV) in cluttered environments is a challenging issue owing to the unknown motion intention of the target and the complex moving environments. As the complexity of the environment increases, stable and secure target tracking is increasingly difficult to guarantee. To address the issue, this paper proposes a stable quadrotor tracking solution. The proposed solution contains two parts: target motion prediction and tracking path searching. The target motion prediction method predicts the future target motion based on the obtained target observations while considering observation noise and prediction errors. The tracking path searching method utilizes a sampling-based search method, using the homotopy of paths to ensure that the tracking path and the target position are in the same space. Finally, simulations, real-world experiments and statistical analysis verify the correctness and effectiveness of the proposed approach. © 2022 IEEE.

关键词： Antennas

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A Graph Reconstruction by Dynamic Signal Coefficient for Fault Classification

arXiv

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arXiv 2023年

作者： He, Wenbin Mao, Jianxu Wang, Yaonan Li, Zhe Fang, Qiu Wu, Haotian The College of Electrical and Information Engineering The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China

To improve the performance in identifying the faults under strong noise for rotating machinery, this paper presents a dynamic feature reconstruction signal graph method, which plays the key role of the proposed end-to-end fault diagnosis model. Specifically, the original mechanical signal is first decomposed by wavelet packet decomposition (WPD) to obtain multiple sub-bands including coefficient matrix. Then, with originally defined two feature extraction factors MDD and DDD, a dynamic feature selection method based on L2 energy norm (DFSL) is proposed, which can dynamically select the feature coefficient matrix of WPD based on the difference in the distribution of norm energy, enabling each sub-signal to take adaptive signal reconstruction. Next the coefficient matrices of the optimal feature sub-bands are reconstructed and reorganized to obtain the feature signal graphs. Finally, deep features are extracted from the feature signal graphs by 2D-Convolutional neural network (2D-CNN). Experimental results on a public data platform of a bearing and our laboratory platform of robot grinding show that this method is better than the existing methods under different noise intensities. Copyright © 2023, The Authors. All rights reserved.

关键词： Feature extraction

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Double-layer Descriptors and High-dimensional Search Mechanisms for Partial Point Cloud Registration

Double-layer Descriptors and High-dimensional Search Mechani...

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Chinese Automation Congress (CAC)

作者： Zhiyu Wang Qiu Fang Yaonan Wang Hong Lu Jun Ye National Engineering Research Center for Robot Visual Perception and Control Technology School of Electrical and Information Engineering Hunan University Changsha Hunan China

Partial point cloud registration is an essential preprocessing technique to generate complete 3D shapes that aim to transform partial scans into a common coordinate system. Existing methods that utilize geometric alignment rarely combine local and global information, which results in many incorrect correspondences. In the paper, a two-layer descriptor and a high-dimension searching approach (DDHSM) are utilized to extract and select the correct correspondences. Firstly, in the first layer, the Fast Point Feature Histogram (FPFH) is used to describe the feature of every point with high-dimension information based on its robustness and fastness. Then a high-dimensional search is considered to extract the initial corresponding set. In the second layer, global information is introduced to find the correct correspondences. For each point pair in the initial corresponding set, the normal angles are compared for all remaining points that satisfy the distance requirement. Finally, the singular value decomposition (SVD) method is implemented to compute the rigid transformation based on the updated corresponding set. Experimental results and comparisons with state-of-the-art methods demonstrate the effectiveness and feasibility of our approach.

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