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IEEE International Conference on Unmanned Systems (ICUS)

作者： Haitao Xu Hanqi Wang Xueshi Zhang Pengfei Zhou Huawei Liang Institutes of Physical Science and Information Technology Anhui University Hefei China Chinese Academy of Sciences Hefei Institutes of Physical Science Hefei China Anhui Engineering Laboratory for Intelligent Driving Technology and Application Hefei China Chinese Academy of Sciences Innovation Research Institute of Robotics and Intelligent Manufacturing Hefei China

Simultaneous Localization And Mapping (SLAM) is a crucial technology for mobile robots to locate themselves when working in a location environment. However, when a large number of dynamic objects appear in the environment, the positioning and mapping results of the robot will be affected. At present, online real-time removal algorithms can effectively solve such problems. Therefore, this paper proposes a dynamic object removal algorithm based on multi-scale spatial information, which identifies and eliminates moving objects in the environment during self-localization and environmental modeling. In this paper, the Inertial Measurement Unit (IMU) data is used to pre-liminarily judge the robot's position and attitude transformation, and the dynamic target distance is combined to adjust the target feature extraction scale, and modify the dynamic object detection conditions to screen objects with high confidence. To remove misjudgment information caused by irregular objects in the environment, road information is used to remove misjudgment information and obtain dynamic object coordinate information in the environment. Through quantitative and qualitative experiments, it has been proven that this algorithm can improve the positioning accuracy of robots in urban road scenes and optimize environmental models. This algorithm reduces Absolute Pose Error by 0.11032m.

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An Improved Feature-Based Visual Slam Using Semantic Information

An Improved Feature-Based Visual Slam Using Semantic Informa...

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IEEE Information technology, Networking, Electronic and Automation Control Conference

作者： Songyu Ma Huawei Liang Hanqi Wang Tiejuan Xu Anhui Jianzhu University Hefei China Chinese Academy of Sciences Hefei Institutes of Physical Science Hefei China Chinese Academy of Sciences Innovation Research Institute of Robotics and Intelligent Manufacturing Hefei China Anhui Engineering Laboratory for Intelligent Driving Technology and Application Hefei China University of Science and Technology of China Hefei China

The traditional visual slam method for feature extraction is single and has poor robustness. This paper proposes an improved feature-based SLAM (Simultaneous localization and mapping) by adding weights to the features of objects matching the same semantic category and incorporating semantic information into loop closure detection. The basic idea is to use the deep neural network YOLOV5 to classify things, associate feature points with objects appearing in the bounding box, and thus assign the feature points to the semantic labels of these objects. In the feature matching process of the SLAM algorithm, the matching of feature points with the same semantic label will be weight, which increases the matching of similar features on the same category of objects, and at the same time intefrates semantic information into loop detection to improve the accuracy of loop closure detection. The test results show that the absolute trajectory error of the improved algorithm is more minor, the pose estimation accuracy is higher, and the tracking robustness can be effectively improved.

关键词： Training Visualization Simultaneous localization and mapping Semantics Pose estimation Neural networks Object detection

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Univariate Thiele Type Continued Fractions Rational Interpolation with Parameters 15th

Univariate Thiele Type Continued Fractions Rational Interpol...

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15th International Conference on intelligent Computing, ICIC 2019

作者： Zou, Le Song, Liang-Tu Wang, Xiao-Feng Huang, Qian-Jing Chen, Yan-Ping Tang, Chao Zhang, Chen Anhui Provincial Engineering Laboratory of Big Data Technology Application for Urban Infrastructure Department of Computer Science and Technology Hefei University Hefei230601 China Institute of Intelligent Machines Hefei Institutes of Physical Science Chinese Academy of Sciences P. O. Box 1130 Hefei230031 China University of Science and Technology of China Hefei230027 China Department of Environmental Engineering Hefei University HefeiAnhui230601 China

ISBN: (纸本)9783030267650

Thiele-type continued fractions interpolation may be the classical rational interpolation and plays critical role in image interpolation and numerical analysis. Different from the traditional method, a new Thiele type continued fractions rational interpolation method with parameters was presented to address the interpolation problem efficiently. Firstly, in order to gain neat expressions in terms of inverse differences, we chose the multiplicity of the points strategically. Secondly, we constructed a univariate Thiele type continued fractions rational interpolation with parameters, which can satisfy the interpolation condition. We also discussed the interpolation algorithm, interpolation theorem. Numerical examples were given to show that the presented method achieves state-of-the-art performance. © 2019, Springer Nature Switzerland AG.

关键词： Interpolation

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A strained π-extendedcycloparaphenylene carbon nanoring

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Chinese Chemical Letters 2024年第5期35卷 171-174页

作者： Kang Wei Jiayu Li Wen Zhang Bing Yuan Ming-De Li Pingwu Du Key Laboratory of Precision and Intelligent Chemistry Anhui Laboratory of Advanced Photon Science and TechnologyDepartment of Materials Science and EngineeringUniversity of Science and Technology of ChinaHefei 230026China Department of Chemistry and Key Laboratory for Preparation and Application of Ordered Structural Materials of Guangdong Province Shantou UniversityShantou 515063China

Herein,we report the facile synthesis of a highly strained hexabenzocoronene-containing carbon nanoring,cyclo[4]-paraphenylene[2]-2,11-hexabenzocoronenylene([4,2]CPHBC),as the segment of a[10,10]single-walled carbon nanotube([10,10]SWNT).[4,2]CPHBC was synthesized based on the platinummediated assembly of diborylbiphenyl and diborylhexabenzocoronene,forming a tetranuclear platinum complex,followed by reductive *** nanoring molecule was confirmed by NMR and HRMS,and its photophysical properties were studied using steady-state and time-resolved ***,the selective supramolecular host-guest interaction between[4,2]CPHBC and C_(60) was also investigated.

关键词： [10]CPP Hexabenzocoronene Fullerene Supramolecular chemistry

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Efficent Lane Change Path Planning based on Quintic spline for Autonomous Vehicles

Efficent Lane Change Path Planning based on Quintic spline f...

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IEEE International Conference on Mechatronics and Automation

作者： Zhiyuan Li Huawei Liang Pan Zhao Shaobo Wang Hui Zhu Chinese Academy of Sciences (CAS) Hefei Institutes of Physical Science Hefei China University of Science and Technology of China Hefei China Anhui Engineering Laboratory for Intelligent Driving Technology and Application Hefei China Chinese Academy of Sciences Innovation Research Institute of Robotics and Intelligent Manufacturing Hefei China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

This paper proposes a lane change path planning method for Autonomous Vehicles (AVs) driving in structured environments. Due to the complexity of dynamically changing structured environment, the path planner generally requires to generate a safe and smooth path in a short time when changing lanes. Therefore, we propose an efficient lane change path planning method, which can take into account both the curvature and heading angle of the planned path, ensuring the safety and stability of the lane change maneuver. It builds upon existing method using quintic spline with second-order geometric (G 2 -) continuity in a Frenet coordinate system. By calculating the optimal prediction time interval of the lane change maneuver, the heading angle was kept within a safe range. In order to improve the real-time performance, we use road prior information to optimize the selection of sampling points, effectively reducing the number of candidate paths. In addition, beyond the sampling points, the problem of continuous lane change is solved by adding mid-adjust point and target point, so that AVs have the ability to complete complex movements. In an urban environment, the proposed method is tested on our experimental autonomous vehicle equipped with a modular ROS architecture. Experimental results show that the proposed algorithm can generate complex motion paths efficiently, and the curvature and heading angle of the planned path are continuous, which effectively improves the efficiency and stability of path planning.

关键词： Roads Path planning Real-time systems Planning Splines (mathematics) Vehicle dynamics Autonomous vehicles

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Rapid Generation of Challenging Simulation Scenarios for Autonomous Vehicles Based on Adversarial Test

Rapid Generation of Challenging Simulation Scenarios for Aut...

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IEEE International Conference on Mechatronics and Automation

作者： Xiaokun Zheng Huawei Liang Biao Yu Bichun Li Shaobo Wang Zhilei Chen Chinese Academy of Sciences Hefei Institutes of Physical Science Heifei Anhui China University of Science and Technology of China Heifei Anhui China Anhui Engineering Laboratory for Intelligent Driving Technology and Appllication Hefei Anhui China Chinese Academy of Sciences Innovation Research Institute of Robotics and Intelligent Manufacturing Hefei Anhui China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

As the development of the autonomous vehicles, the test and evaluation of the autonomy of autonomous vehicles has receiving considerable attentions from both academic and industrial research fields recently. How to rapid identify the performance boundaries of autonomous vehicles and then to accelerate the testing has been considered as one of the most important problems. Simulation test and challenging scenarios are considered as two effective ways to solve above problems. In this research, a framework of rapid generation of challenging simulation scenarios based on adversarial test was proposed. An optimization model based on newly developed indicators, i.e., safety, smoothness, sharpness and smartness, was proposed to assess the autonomy of autonomous vehicles. Due to the high dimensionality of the configuration space and computation complexity of the optimization problem, a quantum genetic algorithm was employed to solve the optimization problem owing to its high search ability and lower population size required. A simulation system based on Prescan, Carsim and Simulink was built to validate the effectiveness of the proposed method. Comparative experiments also were conducted to illustrate the efficiency of the proposed optimization algorithm.

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Obstacle-surmounting Analysis of a Novel Deformable Wheel-track Composite Walking Platform

Obstacle-surmounting Analysis of a Novel Deformable Wheel-tr...

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International Conference on Autonomous Robots and Agents, ICARA

作者： Wang Kun Liang Huawei Chinese Academy of Sciences Hefei Institutes of Physical Science Hefei China University of Science and Technology of China Hefei China Hefei China Anhui Engineering Laboratory for Intelligent Driving Technology and Application Hefei China Chinese Academy of Sciences Innovation Research Institute of Robotics and Intelligent Manufacturing Hefei China Hefei China

Based on high mobility requirements of unmanned ground platforms in various environments and combining the advantages of traditional wheeled, crawler and legged walking mechanisms, a novel deformable wheel-track composite walking mechanism with multi-movement modes is proposed,obtaining better obstacle-surmounting performances than the famous reconfigurable wheel-track mechanism(RWT type) in recent years. The walking mechanism has two stable forms of round wheel configuration and prolate polygon configuration with three modes of wheel rolling, track movement and gait rotation, which are respectively suitable for travelling on hard roads at high speeds, moving on soft earth with low contact pressure and crossing obstacles. Design of the innovative structure and a platform equipped with the novel machines is carried out. Subsequently, the platform's obstacle surmounting performance is analyzed through dynamic modelling and calculation. Ultimately to verify the advantages of the machine and its design rationality, comparative simulation experiments of obstacle-surmounting performances is implemented in the multi-body simulation environment,setting up obstacle models and building experimental platform models integrating this machine and the RWT type machine respectively.

关键词： Legged locomotion Deformable models Analytical models Adaptation models Tracking Dynamics Crawlers

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A New Adaptive Noise Covariance Matrices Estimation and Filtering Method: application to Multi-Object Tracking

arXiv

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arXiv 2021年

作者： Jiang, Chao Wang, Zhiling Tan, Shuhang Liang, Huawei The Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei230031 China The University of Science and Technology of China Hefei230026 China The Anhui Engineering Laboratory for Intelligent Driving Technology and Application Hefei230031 China The Innovation Research Institute of Robotics and Intelligent Manufacturing Chinese Academy of Sciences Hefei230031 China

Kalman filters are widely used for object tracking, where process and measurement noise are usually considered accurately known and constant. However, the exact known and constant assumptions do not always hold in practice. For example, when lidar is used to track noncooperative targets, the measurement noise is different under different distances and weather conditions. In addition, the process noise changes with the object's motion state, especially when the tracking object is a pedestrian, and the process noise changes more frequently. This paper proposes a new estimation-calibration-correction closed-loop estimation method to estimate the Kalman filter process and measurement noise covariance matrices online. First, we decompose the noise covariance matrix into an element distribution matrix and noise intensity and improve the Sage filter to estimate the element distribution matrix. Second, we propose a calibration method to accurately diagnose the noise intensity deviation. We then propose a correct method to adaptively correct the noise intensity online. Third, under the assumption that the system is detectable, the unbiased and convergence of the proposed method is mathematically proven. Simulation results prove the effectiveness and reliability of the proposed method. Finally, we apply the proposed method to multiobject tracking of lidar and evaluate it on the official KITTI server. The proposed method on the KITTI pedestrian multiobject tracking leaderboard (http://***/datasets/kitti/eval_***) surpasses all existing methods using lidar, proving the feasibility of the method in practical applications. This work provides a new way to improve the performance of the Kalman filter and multiobject tracking. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical radar

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UGV-UAV Cooperative 3D Multi-Object Tracking Based on Multi-Source Data Fusion

UGV-UAV Cooperative 3D Multi-Object Tracking Based on Multi-...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Mingjia Zhang Huawei Liang Pengfei Zhou Chinese Academy of Sciences Hefei Institutes of Physical Science Hefei China University of Science and Technology of China Hefei China Nanjing Polytechnic Institute Nanjing China Anhui Engineering Laboratory for Intelligent Driving Technology and Application Hefei China Innovation Research Institute of Robotics and Intelligent Manufacturing Chinese Academy of Sciences Hefei China

Unmanned aerial vehicles (UAVs) and Unmanned ground vehicles (UGV s) have complementary sensing characteristics, and their cooperative sensing can effectively solve the problems of target loss due to view occlusion or distance in multi-target tracking tasks. In this paper, we propose a track by detection framework based on a multi-source data fusion approach. In the detection phase, a modified ImvoxelN et network with attention mechanism is proposed to fuse the multi-view image data of unmanned vehicles and UAVs to estimate the position and size of the target. In the tracking stage, the method involves correlation processing of both 2D and 3D detection data. It utilizes an interactive multi-mode unscented Kalman filter (IMM-UKF) algorithm that incorporates the Minimum-update Successive Shortest Path (muSSP) method to enhance the accuracy and real-time performance of dynamic target tracking. The experimental results demonstrate the effectiveness of the proposed approach in significantly improving the performance of multi-target tracking tasks.

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Saliency detection via bidirectional absorbing Markov chain

arXiv

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arXiv 2018年

作者： Jiang, Fengling Kong, Bin Adeel, Ahsan Xiao, Yun Hussain, Amir Institute of Intelligent Machines Chinese Academy of Sciences Hefei230031 China University of Science and Technology of China Hefei230026 China Hefei Normal University Hefei230061 China Anhui Engineering Laboratory for Intelligent Driving Technology and Application Hefei230088 China University of Stirling StirlingFK9 4LA United Kingdom Anhui University Hefei230601 China

Traditional saliency detection via Markov chain only consider boundaries nodes. However, in addition to boundaries cues, background prior and foreground prior cues play a complementary role to enhance saliency detection. In this paper, we propose an absorbing Markov chain based saliency detection method considering both boundary information and foreground prior cues. The proposed approach combines both boundaries and foreground prior cues through bidirectional Markov chain. Specifically, the image is first segmented into superpixels and four boundaries nodes (duplicated as virtual nodes) are selected. Subsequently, the absorption time upon transition node's random walk to the absorbing state is calculated to obtain foreground possibility. Simultaneously, foreground prior as the virtual absorbing nodes is used to calculate the absorption time and obtain the background possibility. Finally, two obtained results are fused to obtain the combined saliency map using cost function for further optimization at multi-scale. Experimental results demonstrate the outperformance of our proposed model on 4 benchmark datasets as compared to 17 state-of-the-art methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Cost functions

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