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第40届中国控制会议

作者： Lei Xu Jiexi Liu Bo Chen Beijing Institute of Technology School of Automation Key Laboratory of Complex System Intelligent Control and Decision

Temporal Action Detection is a research hotspot in Video *** is necessary not only to give the specific moments of the beginning and end of each action instance in the video,but also to give the category of the action *** present,most of the methods in temporal action detection are divided into two steps:The video is divided into a series of video clips to determine whether each clip is an action instance,and the fragments that are not an action instance are deleted;Segments that may be action instances are then classified to get the final *** present,the difficulties in action detection research mainly include the following two points:1) The boundary is not *** from action recognition,action detection requires precise positioning,but an action in life is often not very *** is also the reason why the mean average precision(mAP) of action detection is low at present.2) The time span is *** life,an action often spans a very long *** movements such as waving can last for a few seconds,while long movements such as rock climbing or cycling can last for tens of minutes,which makes it extremely difficult for us to extract *** view of the above difficulties,this paper proposes a large receptive field boundary matching network(LRFBMN) model which takes advantage of the relationship between proposals to improve the accuracy of proposal *** model is mainly divided into two parts:1) Clipping feature map is processed by large kernel convolution,and then proposal feature is generated by ROI-pooling;2) The proposals are arranged in a certain order to form a fixed graph,and the information exchange between graph nodes is realized by using convolution with *** experiments,this model is 2.35% higher than baseline and 1.06% higher than state-of-the-art in THUMOS14 data set.

关键词： Temporal Action Detection Video Understanding Proposal Large Receptive Field

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ADFNet: A two-branch robotic grasping network based on attention mechanism

ADFNet: A two-branch robotic grasping network based on atten...

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第40届中国控制会议

作者： Pengwei Xie Nan Hao Bo Chen Beijing Institute of Technology School of Automation Key Laboratory of Complex System Intelligent Control and Decision

One of the challenges of RGB-D-based robotic grasping technology is how to make full use of these two complementary heterogeneous data sources while ensuring real-time performance. The existing robotic grasping methods mainly extract information from single-mode images or use a one-branch network to process RGB and depth images. These methods are insufficient in fully fusing the effective information of the two modes, which limits the anti-jamming performance. In this work,we propose Attention Dense Fusion Network（ADFNet）, a novel RGB-D based robotic grasping system that directly predicts the optimal grasping pose from RGB-D images. Our system uses a two-branch network with a heterogeneous framework that processes RGB and depth image information separately and retain the original structure of each data source. After applying dense fusion networks at different scales, the high-dimensional features in the RGB and depth branches are embedded and fused at the pixel level. Besides, we incorporate attention mechanisms to effectively suppress the independent background regions of the feature map and enhance the significant features, which improves the prediction accuracy. We conduct qualitative and quantitative experiments on the standard Cornell Grasp Dataset. The experimental results show that ADFNet can effectively improve the prediction accuracy to 98.9 %, which is better than existing methods while ensuing real-time performance.

关键词： robotic grasping RGB-D attention mechanism

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Smooth quadrotor trajectory generation for tracking a moving target in cluttered environments

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Science China(Information Sciences) 2021年第7期64卷 132-147页

作者： Lele XI Zhihong PENG Lei JIAO Ben M.CHEN School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Peng Cheng Laboratory Department of Mechanical and Automation Engineering The Chinese University of Hong Kong

In this paper, we present a trajectory generation method of a quadrotor, based on the optimal smoothing B-spline, for tracking a moving target with consideration of relative tracking pattern or limited field of view of the onboard sensor in cluttered environments. Compared to existing methods, safe flying zone,vehicle physical limits, and smoothness are fully considered to guarantee flight safety, kinodynamic feasibility, and tracking performance. To tackle the cluttered environments, a parallel particle swarm optimization algorithm is applied to find the feasible waypoints that the generated trajectory should be as close to as possible, with consideration of the target's future state as well as obstacles to trade off the tracking performance and flight safety. Then, a sequential motion planning method, considering the above constraints, is applied and embedded into a cost function for solving the problem of robust tracking trajectory generation for the quadrotor via a convex optimization approach. The feasibility and effectiveness of the proposed method are verified by numerical simulations.

关键词： quadrotor target tracking trajectory generation B-spline convex optimization

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An attention-based RGBD dual-branch gesture recognition network

An attention-based RGBD dual-branch gesture recognition netw...

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第40届中国控制会议

作者： Bo Chen Pengwei Xie Nan Hao Beijing Institute of Technology School of Automation Key Laboratory of Complex System Intelligent Control and Decision

In this work,we use a hierarchical architecture based on detector-classifier for gesture recognition *** the operation of the architecture,the detector,which is essentially the switch of the classifier,is always *** the output of the detector is true,then the classifier is activated and returns a classification label for the input video *** work focuses on the improvement of detectors and *** the detector,we introduce an attention mechanism to guide the network to focus on the space and channel where the gesture is *** the classifier,based on the RGB information stream,we use an independent branch to extract the features of the depth stream,and finally merge the two *** gestures move in a three-dimensional space,depth information can make up for the lack of RGB *** show that on the Egogesture test set,our detector achieves 98.86% accuracy on RGB input,while the classifier achieves 93.85% *** the same time,our gesture recognition architecture can fully meet the real-time requirements.

关键词： Gesture Recognition RGBD feature fusion attention mechanism real-time

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Torque Compensation Model and Touchdown Detection Model of the Hydraulic Quadruped Robot controlled by VMC

Torque Compensation Model and Touchdown Detection Model of t...

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Chinese control and decision Conference, CCDC

作者： Ranjiang Wang Jiangbo Zhao Junzheng Wang Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology School of Automation Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665478977

In this paper, according to the different dynamic models of the support phase and the swing phase, the joint torque compensation of the support phase and the swing phase are given to compensate the joint torque of the hydraulic quadruped robot controlled by the virtual model control(VMC). This compensation can increase the tracking effect of the foot end on the swing trajectory, reduce the elasticity and damping coefficient of the virtual model method, and increase the flexibility of the leg. Then this paper establishes the touchdown detection function based on the joint torque obtained by the Lagrange dynamics equation and the joint torque obtained by the force sensor to determine the touch state of the foot of the quadruped robot to switch the phase of the leg. At the end of this paper, simulation and experiment prove that the compensation model and touchdown detection function model have feasibility and correctness.

关键词： Legged locomotion Damping Torque Switches Hydraulic systems Elasticity Mathematical models

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Estimation of smoke echo signal using single-photon lidar 13

Estimation of smoke echo signal using single-photon lidar

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13th International Conference on Information Optics and Photonics, CIOP 2022

作者： Zhang, Yinbo Li, Sining Sun, Jianfeng Jiang, Peng Zhou, Shuaijun Zhang, Xin Hou, Yue Zhang, Hailong National Key Laboratory of Science and Technology on Tunable Laser Institute of Opto-Electronic Harbin Institute of Technology Heilongjiang Harbin150001 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Aerospace Automatic Control Institute Beijing100854 China

ISBN: (纸本)9781510660632

The non-uniform distribution of smoke and laser spot seriously limits the imaging ability of single-photon lidar through smoke. To this end, based on the collision theory between photons and smoke particles, this paper establishes the time-domain distribution model of scattered photons (Gamma), which considers the lidar system parameters and the characteristics of smoke particles. The shape parameter and inverse scale parameter are defined as the maximum scattering number K and the average scattering number β, respectively. The indoor test effectively illustrates the estimation ability of the model for smoke. The parameter estimation results show that the average scattering number β and the maximum scattering number K increase linearly with the increase of attenuation coefficient. This study is of great significance for the suppression of smoke backscattering and is expected to improve the weather adaptability of single-photon lidar. © 2022 SPIE.

关键词： Backscattering

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Distributed solver for linear matrix inequalities: an optimization perspective

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control Theory and Technology 2021年第4期19卷 507-515页

作者： Weijian Li Wen Deng Xianlin Zeng Yiguang Hong Department of Automation University of Science and Technology of ChinaHefei 230027AnhuiChina Key Lab of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

In this paper,we develop a distributed solver for a group of strict(non-strict)linear matrix inequalities over a multi-agent network,where each agent only knows one inequality,and all agents co-operate to reach a consensus solution in the intersection of all the feasible *** formulation is transformed into a distributed optimization problem by introducing slack variables and consensus ***,by the primal–dual methods,a distributed algorithm is proposed with the help of projection operators and derivative ***,the convergence of the algorithm is analyzed,followed by illustrative simulations.

关键词： Distributed computation Distributed optimization Linear matrix inequalities Primal-dual method

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Application and Performance Evaluation of Object Detection Technology Based on Computer Vision

Application and Performance Evaluation of Object Detection T...

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Asian control Conference

作者： WeiXue Li Hang Zhang Cong Wan JiaWen Shi TingRu Li National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Talent Exchange Center Ministry of Industry and Information Technology P.R.C. Beijing China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

In light of the challenges posed by the variability of industrial part shapes, weak texture information, and surface reflections in current industrial vision inspection, traditional methods such as feature descriptors and template matching are inadequate. This paper innovatively proposes a machine learning object detection method, establishes robust stable features for weakly textured industrial parts, and evaluates the performance of the model and feature selection in combination with actual fuel tank cap detection tasks. Firstly, we construct a dataset of fuel tank cap targets and establish a comprehensive and relatively stable feature dataset, including geometric features, texture features, and color features. Secondly, through ablation experiments and comparative experiments, we conduct intelligent per-formance testing on model detection accuracy, parameter selection, and feature contribution. Finally, the evaluation results demon-strate that the support vector machine (SVM) model exhibits the best detection performance after feature selection, with a detection accuracy of 99.0% under the optimal parameter settings validated through experiments.

关键词： Support vector machines Adaptation models Image color analysis Computational modeling Fuel storage Object detection Inspection

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Operating Health State Prediction and Evaluation of Excitation Unit Based on GMM and LSTM 3rd

Operating Health State Prediction and Evaluation of Excitati...

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3rd China intelligent Robotics Annual Conference, CCF CIRAC 2022

作者： Ma, Yinxing Yang, Peihao Lv, Gang Deng, Shibin Jiao, Shangbin Li, Yujun Wu, Xiaohui Zhang, Jing Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Xi’an Thermal Power Research Institute Co. Ltd. Xi’an710054 China Huaneng Weihai Power Generation Co. Ltd. Wei’hai264200 China

ISBN: (纸本)9789819903009

The excitation unit is the weak link in the generator operation since it produces internal deterioration under long-term operation. To evaluate the health condition of the key excitation unit and generate warning information in advance, this work proposes a health assessment method based on the Gaussian mixture model (GMM) and LSTM neural network. Firstly, the weights of each type of data will be determined by obtaining the electrical parameter data of the generator excitation unit from the SIS system, using the infrared image data of carbon brush and excitation transformer based on infrared image acquisition system, and the correlation between each electrical parameter data and temperature on account of the MIC correlation analysis method. On the top of it, LSTM neural network prediction model is established. And establish a GMM-based health benchmark model based on the data collected in the field during healthy operation, and design the health decline index HDI using the Marxist distance for evaluating the health status and deterioration degree of the unit. Finally, the method of this paper is validated by the 2022 operation data of a thermal power plant in Weihai, which proved that this method can provide a basis for regular maintenance and early identification of faults in the power plan and quantifying the degradation degree of the excitation unit under long-term operation and making early warning before the abnormal occurrence of the unit. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deterioration

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Development of a 3-RRS Micromanipulator Based on Origami-Inspired Spherical Joint

Development of a 3-RRS Micromanipulator Based on Origami-Ins...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Haoqi Han Xiaoming Liu Yan Chen Hao Pang Xiaoqing Tang Dan Liu Qiang Huang Tatsuo Arai Beijing Advanced Innovation Center for Intelligent Robots and Systems and School of Mechatronical Engineering Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Department of Micro-Nano Electronics Shanghai Jiao Tong University China Center for Neuroscience and Biomedical Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In recent years, micromanipulation technology has achieved extensive applications in industry and life science. Improving the precision and bandwidth of the micromanipulator and simultaneously reducing size, weight, and cost pose significant challenges to the existing micromanipulator design and fabrication methods. Here, we propose a 3-RRS micromanipulator with an origami-inspired spherical joint based on the PC-MEMS process, aiming for miniaturization and cost-effectiveness. The spherical joint allows rotations of 140° around the x-axis approximately, 140° around the y-axis approximately, and 20° around the z-axis approximately. The micromanipulator has weights of 0.8 g, dimensions of 16 mm × 16 mm × 22 mm, and workspace of 0.7 mm 3 . The end platform of the micromanipulator can be equipped with various effectors to accomplish different kinds of tasks. Experimental results validated its high precision and bandwidth, exhibiting its potential to perform intricate micromanipulation tasks.

关键词： Industries Fabrication Costs Micromanipulators Design methodology Bandwidth Life sciences

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