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arXiv 2022年

作者： Chen, Song Cai, Shengze Chen, Tehuan Xu, Chao Chu, Jian The School of Mathematical Sciences Zhejiang University Zhejiang Hangzhou310027 China School of Mechanical Engineering and Mechanics Ningbo University Zhejiang Ningbo315211 China Ningbo Artificial Intelligence Institute Shanghai Jiao Tong University Zhejiang Ningbo315000 China The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang Hangzhou310027 China Huzhou Institute of Zhejiang University Zhejiang Huzhou313000 China

In this paper, we propose a novel nonlinear observer based on neural networks, called neural observer, for observation tasks of linear time-invariant (LTI) systems and uncertain nonlinear systems. In particular, the neural observer designed for uncertain systems is inspired by the active disturbance rejection control, which can measure the uncertainty in real-time. The stability analysis (e.g., exponential convergence rate) of LTI and uncertain nonlinear systems (involving neural observers) are presented and guaranteed, where it is shown that the observation problems can be solved only using the linear matrix inequalities (LMIs). Also, it is revealed that the observability and controllability of the system matrices are required to demonstrate the existence of solutions of LMIs. Finally, the effectiveness of neural observers is verified on three simulation cases, including the X-29A aircraft model, the nonlinear pendulum, and the four-wheel steering vehicle. Copyright © 2022, The Authors. All rights reserved.

关键词： Observability

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Design of a curled hyper-redundant manipulator and the motion control with tip-following algorithm

Design of a curled hyper-redundant manipulator and the motio...

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Chinese control and Decision Conference, CCDC

作者： Aoshun Zhang En Li Feng Zhang Rui Guo Mingrui Luo Yuwei Zhang School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Engineering Laboratory for Intelligent Industrial Vision CAS Beijing China State Grid Intelligent Technology Co. Ltd. Shandong China State Grid Shandong Electric Power Company Jinan Power Supply Company Shandong China

In order to meet the operational needs in some narrow environments, the hyper-redundant snake-shaped manipulator has received extensive attention and has been widely studied due to its compact shape and multiple degrees of freedom. At present, the research of hyper-redundant manipulator mainly focuses on the straight push platform. Considering the limitation of working space, this paper designed a hyper-redundant manipulator delivered by a curled turntable. According to the characteristics of turntable delivery, a tip-following algorithm based on curve fitting and a tip-following strategy based on terminal posture record are proposed. Finally, with the algorithm applied to the physical robot we made, we successfully realized the tip-following motion control of the hyper-redundant manipulator.

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Sequence-to-Sequence Voice Reconstruction for Silent Speech in a Tonal Language

arXiv

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arXiv 2021年

作者： Li, Huiyan Lin, Haohong Wang, You Wang, Hengyang Zhang, Ming Gao, Han Ai, Qing Luo, Zhiyuan Li, Guang The State Key Laboratory of Industrial Control Technology Institute of Cyber Systems and Control Zhejiang University Hangzhou310027 China Department of Computer Science Royal Holloway University of London Egham Hill Surrey EghamTW20 0EX United Kingdom

Silent Speech Decoding (SSD), based on articulatory neuromuscular activities, has become a prevalent task of Brain-Computer Interface (BCI) in recent years. Many works have been devoted to decoding surface electromyography (sEMG) from articulatory neuromuscular activities. However, restoring silent speech in tonal languages such as Mandarin Chinese is still difficult. This paper proposes an optimized Sequence-to-Sequence (Seq2Seq) approach to synthesize voice from the sEMG-based silent speech. We extract duration information to regulate the sEMG-based silent speech using the audio length. Then, we provide a deep-learning model with an encoderdecoder structure and a state-of-art vocoder to generate the audio waveform. Experiments based on six Mandarin Chinese speakers demonstrate that the proposed model can successfully decode silent speech in Mandarin Chinese and achieve a character error rate (CER) of 6.41% on average with human evaluation. Copyright © 2021, The Authors. All rights reserved.

关键词： Brain computer interface

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RaLL: End-to-end radar localization on Lidar map using differentiable measurement model

arXiv

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arXiv 2020年

作者： Yin, Huan Chen, Runjian Wang, Yue Xiong, Rong The State Key Laboratory of Industrial Control and Technology Zhejiang University Hangzhou China The Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

Compared to the onboard camera and laser scanner, radar sensor provides lighting and weather invariant sensing, which is naturally suitable for long-term localization under adverse conditions. However, radar data is sparse and noisy, resulting in challenges for radar mapping. On the other hand, the most popular available map currently is built by lidar. In this paper, we propose an end-to-end deep learning framework for Radar Localization on Lidar Map (RaLL) to bridge the gap, which not only achieves the robust radar localization but also exploits the mature lidar mapping technique, thus reducing the cost of radar mapping. We first embed both sensor modals into a common feature space by a neural network. Then multiple offsets are added to the map modal for exhaustive similarity evaluation against the current radar modal, yielding the regression of the current pose. Finally, we apply this differentiable measurement model to a Kalman Filter (KF) to learn the whole sequential localization process in an end-to-end manner. The whole learning system is differentiable with the network based measurement model at the front-end and KF at the back-end. To validate the feasibility and effectiveness, we employ multi-session multi-scene datasets collected from the real world, and the results demonstrate that our proposed system achieves superior performance over 90km driving, even in generalization scenarios where the model training is in UK, while testing in South Korea. We also release the source code publicly 1 Copyright © 2020, The Authors. All rights reserved.

关键词： Optical radar

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F-Siamese Tracker: A Frustum-based Double Siamese Network for 3D Single Object Tracking

F-Siamese Tracker: A Frustum-based Double Siamese Network fo...

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2020 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Hao Zou Jinhao Cui Xin Kong Chujuan Zhang Yong Liu Feng Wen Wanlong Li Institute of Cyber-Systems and Control Zhejiang University Zhejiang China State Key Laboratory of Industrial Control Technology and Institute of Cyber-Systems and Control Zhejiang University Zhejiang China Huawei Noah’s Ark lab

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

This paper presents F-Siamese Tracker, a novel approach for single object tracking prominently characterized by more robustly integrating 2D and 3D information to reduce redundant search space. A main challenge in 3D single object tracking is how to reduce search space for generating appropriate 3D candidates. Instead of solely relying on 3D proposals, firstly, our method leverages the Siamese network applied on RGB images to produce 2D region proposals which are then extruded into 3D viewing frustums. Besides, we perform an on-line accuracy validation on the 3D frustum to generate refined point cloud searching space, which can be embedded directly into the existing 3D tracking backbone. For efficiency, our approach gains better performance with fewer candidates by reducing search space. In addition, benefited from introducing the online accuracy validation, for occasional cases with strong occlusions or very sparse points, our approach can still achieve high precision, even when the 2D Siamese tracker loses the target. This approach allows us to set a new state-of-the-art in 3D single object tracking by a significant margin on a sparse outdoor dataset (KITTI tracking). Moreover, experiments on 2D single object tracking show that our framework boosts 2D tracking performance as well.

关键词： Three-dimensional displays Target tracking Two dimensional displays Search problems Object tracking Proposals Intelligent robots

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A Machine Learning Based Risk Identification Method for Illegal Pig Slaughtering

A Machine Learning Based Risk Identification Method for Ille...

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Intelligent Communication and Networking (ICN), International Conference on

作者： Jiajun Miao Yujun Shen Yan Zhang Lingjie Liu Ye Tian Yu Zhao Chunyan Zhou College of Computer Science and Technology Harbin Engineering University Harbin China Hangzhou Hikvision Digital Technology Co. Ltd Hangzhou China China Industrial Control Systems Cyber Emergency Response Team Beijing China Environment and Food and Drug Crime Investigation Detachment of Hangzhou Public Security Bureau Hangzhou China Hangzhou Institute of Technology Xidian University Harbin China Key Laboratory of Peace-Building Big Data of Zhejiang Province Hangzhou China

With the impact of African swine fever, the survival rate of domestic pigs has sharply decreased, and pork prices continue to rise. Many unscrupulous elements obtain illegal profits by avoiding inspection and quarantine, processing sick and dead pigs, and injecting water, etc. Unquarantined meat products pose serious food safety risks. In this context, we propose a machine learning based risk identification method for illegal slaughter of live pigs. Firstly, we use the RetinaNet algorithm to detect live pig transport vehicles and use a dual residual network to Super-Resolution the vehicle area in the detected image to improve facial clarity. Subsequently, the ArcFace algorithm is used to match the facial information with the ex-convicts, and finally, the Location of vehicles passing through, time, frequency and facial analysis results are combined for calculation and scoring and provide the risk warning for illegal slaughter of live pigs.

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Catch Planner: Catching High-Speed Targets in the Flight

arXiv

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arXiv 2023年

作者： Yu, Huan Wang, Pengqin Wang, Jin Ji, Jialin Zheng, Zhi Tu, Jie Lu, Guodong Meng, Jun Zhu, Meixin Shen, Shaojie Gao, Fei The State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China The Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province School of Mechanical Engineering Zhejiang University Hangzhou310027 China Robotics Institute of Zhejiang University Hangzhou310027 China Hong Kong The State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China School of Electrical Engineering Zhejiang University Hangzhou310027 China The Hong Kong University of Science and Technology Guangzhou China

Catching high-speed targets in the flight is a complex and typical highly dynamic task. However, existing methods require manual setting of catching height or time, resulting in lacks of adaptability and flexibility and cannot deal with multiple targets. To bridge this gap, we propose a planning-with-decision scheme called Catch Planner. For sequential decision making, a lightweight policy search method based on deep reinforcement learning is proposed. It is jointly trained with the motion planning and decoupled from physics to speed up training. For motion planning, we propose a trajectory optimization method that jointly optimizes the highly coupled catching time and terminal state. The core is the flexible-terminal constraint transcription. It converts the three unique constraints of catching into differentiable metrics, including equality constraints for terminal position and time, and inequality constraints that enable reasonable terminal position offset and attitude relaxation. In addition, sparse parameterization based on MINCO class considers both dynamic feasibility and collision avoidance constraints. As a result, a generally constrained quadrotor planning problem is transformed into an unconstrained optimization that can be solved reliably and efficiently. We also propose an online iterative optimization method for predicting differentiable trajectories of targets. Catch Planner provides a new paradigm for the combination of learning and planning, where all algorithms can be run in real time onboard at 100hz. Extensive experiments are carried out in real-world and simulated scenes to verify the robustness and expansibility when facing a variety of high-speed flying targets. Copyright © 2023, The Authors. All rights reserved.

关键词： Decision making

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Advanced Robot Programming: a Review

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Current Robotics Reports 2020年第4期1卷 251-258页

作者： Zhou, Zhongxiang Xiong, Rong Wang, Yue Zhang, Jiafan State Key Laboratory of Industrial Control Technology and Institute of Cyber-Systems and Control of Zhejiang Province Zhejiang University Hangzhou China Research Center China Robotics and Discrete Automation ABB Shanghai China

The review presents an overview of advanced robot programming approaches which aims to ease robot programming and speed up the deployment of industrial robots, and then some considerations are shared with respect to requirements in new trends of manufacturing. The new trend of customization along with Industry 4.0 is appearing which is a challenge for robotized systems. The bottleneck is mainly the efficiency of deployment of industrial robots because traditional programming methods are not intuitive and always time-consuming. Advanced robot programming techniques are expected to ease robot programming and make it accessible for non-experts. A review on advanced robot programming is here presented, firstly introducing the background of this research, followed by reviewing literatures in four categories: programming by demonstration for low-level motion, programming by demonstration for high-level task, speech recognition-based and augmented reality-based programming approaches, and finishing on discussing future works.

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Sliding-Mode Design with Disturbance Observer Optimized by Improved HBA Algorithm for Frequency Regulation of Multi-Area Power System

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IAENG International Journal of Applied Mathematics 2022年第4期52卷

作者： Chen, Gonggui Jiang, Zhijin Tan, Hao Zhang, Chaohua Wei, Jinzhu Chen, Wenchen Long, Hongyu Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing University of Posts and Telecommunications Chongqing400065 China Economic and Technology Research Institute State Grid Chongqing Electric Power Company Chongqing401120 China State Grid Chongqing Qianjiang Power Supply Company Chongqing409000 China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China

The intermittency of renewable energy generation and the randomness of power load variations lead to voltage and frequency fluctuations among the interconnected power system. In this study, a control strategy based on sliding mode control theory and disturbance observer is proposed for the multi-area power system with parameter uncertainties to handle load frequency control. By choosing an appropriate integral-type sliding-mode surface and reaching law, a sliding-mode load frequency controller is constructed. In order to reduce the influence of uncertainties, a disturbance observer is designed to estimate lumped disturbances. On this basis, the sliding mode controller is reconstructed to provide better control effect. And the improved honey badger algorithm is used to tune out the optimal parameters of the designed controller. Simulation studies are carried out on a two-region reference system and an unequal capacity three-area power system with nonlinearity connected wind turbine generators to illustrate the favorable performance of the power system under the proposed control strategy. The comparison results show that the proposed control method possesses excellent frequency control ability under the uncertainty of load disturbance, wind power fluctuations and parameter uncertainties. And it also achieves efficient frequency control under a certain range of communication delay. © 2022, IAENG International Journal of Applied Mathematics. All Rights Reserved.

关键词： Wind Turbine Generators

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Efficient two step optimization for large embedded deformation graph based SLAM

Efficient two step optimization for large embedded deformati...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jingwei Song Fang Bai Liang Zhao Shoudong Huang Rong Xiong Centre for Autonomous Systems University of Technology Sydney Broadway Australia State Key Laboratory of Industrial Control Technology and Institute of Cyber-Systems and Control Zhejiang University Zhejiang China

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Embedded deformation graph is a widely used technique in deformable geometry and graphical problems. Although the technique has been transmitted to stereo (or RGB-D) camera based SLAM applications, it remains challenging to compromise the computational cost as the model grows. In practice, the processing time grows rapidly in accordance with the expansion of maps. In this paper, we propose an approach to decouple the nodes of deformation graph in large scale dense deformable SLAM and keep the estimation time to be constant. We observe that only partial deformable nodes in the graph are connected to visible points. Based on this fact, the sparsity of the original Hessian matrix is utilized to split the parameter estimation into two independent steps. With this new technique, we achieve faster parameter estimation with amortized computation complexity reduced from O(n 2 ) to almost O(1). As a result, the computational cost barely increases as the map keeps growing. Based on our strategy, the computational bottleneck in large scale embedded deformation graph based applications will be greatly mitigated. The effectiveness is validated by experiments, featuring large scale deformation scenarios.

关键词： Simultaneous localization and mapping Strain Jacobian matrices Optimization Cameras Deformable models Geometry

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