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2021 China Automation Congress, CAC 2021

作者： Liu, Yonglei Li, Wenjing Faculty of Information Technology Beijing University of Technology Beijing Institute of Artificial Intelligence Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China

ISBN: (纸本)9781665426473

The single-step prediction of the effluent biochemical oxygen demand (BOD) in wastewater treatment process (WWTP) cannot provide the information for future trends, which will affect the decision-making for subsequent control strategies in WWTP. To solve this problem, a radial basis function (RBF) neural network soft-sensing model based on PSO algorithm (PSO-RBF) is proposed for multi-step prediction of the biochemical oxygen demand (BOD) in WWTP. First, we propose an RBF model for multi-step prediction based on MIMO strategy. Then, the PSO algorithm is used to optimize the RBF parameters. Finally, the proposed model is applied to a four-step BOD prediction in WWTP. Experimental results show that this model can better predict BOD in multiple steps compared to traditional models. © 2021 IEEE

关键词： Forecasting

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A Compliant Traction Method of Manipulator Based on Online Calibration of Force Sensor Zero-Point 6

A Compliant Traction Method of Manipulator Based on Online C...

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6th International Conference on Automation, control and Robots, ICACR 2022

作者： Xu, Zhilu Wang, Weijun Feng, Wei Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen China Shenzhen Institute of Advanced Technology Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China

ISBN: (数字)9781665498739

ISBN: (纸本)9781665498739

With the increasing number of cooperative robots, it is becoming increasingly important to improve the safety and operability of human-robot interaction. Installing a six-dimensional force sensor at the end of the manipulator can realize the drag of the manipulator in Cartesian space. A compliant traction method of manipulator based on online calibration of force sensor zero-point is proposed in this paper. Aiming at the problem of "zero drift"of force sensor, after calculating the gravity of the end tool, the zero-point of the force sensor is calibrated online by means of mean processing, so as to obtain more accurate external force. Then, the relationship between the end position of the manipulator and the external force, the end moving speed of the manipulator and the external force is established, and the change of the position and speed of the manipulator is controlled by the external force at the same time. Finally, experiments show the effectiveness of this method and ensure the safety and reliability in the traction process. © 2022 IEEE.

关键词： Manipulators

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Distributed simultaneous localization and mapping algorithm based on partition of space-region

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Xi Tong Gong Cheng Yu Dian Zi Ji Shu/systems Engineering and Electronics 2015年第3期37卷 639-645页

作者： Pei, Fu-Jun Cheng, Yu-Hang Li, Hao-Yang Ju, He-Hua School of Electronic Information & Control Engineering Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligence System Beijing100124 China

To solve the problem of the simultaneous localization and mapping (SLAM) under the complex circumstance, a distributed algorithm of the SLAM based on partition of space-region is proposed considering the respective advantages of centralized configuration and distributed structure. The region is formed according to the angle between two landmarks and the robot, which is designed in case of the collinearity between two landmarks. The landmarks in each region are combined to establish the corresponding observation model. Besides, the position of the robot is obtained by applying the distributed unscented particle filter and the positions of the landmarks are estimated simultaneously by employing the Kalman filter. Meanwhile, the accuracy and the stability are improved through constructing the adjustment of particle distribution during the dynamic reconfiguration process. Eventually, the better real-time capability and filter accuracy of the proposed SLAM algorithm are proved through simulation experiments which are supported by actual data. ©, 2015, Chinese Institute of Electronics. All right reserved.

关键词： Kalman filters

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Detection of Hands-Raising Gestures Using Shape and Edge Features

Detection of Hands-Raising Gestures Using Shape and Edge Fea...

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2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

作者： Hong Liu Yuexian Zou Xiaodong Duan Dengke Gao Key Laboratory of Machine Perception and Intelligence and Key Laboratory of Integrated Micro-system Key Laboratory of Integrated Micro-system Shenzhen Graduate SchoolPeking UniversityChina

ISBN: (纸本)9781424447749

This paper introduces a method of hand-raising gestures detection in indoor environments, using shape and edge features. Past approaches have detected the gestures through recognizing the action for isolated or seated persons. Here, to deal with movements, non-rigidity and partially occlusions of human bodies, the gestures are detected by searching for raised hands and arms rather than recognizing the action. First, background subtraction is employed to obtain body silhouette. And then, according to the particular shape edge features of raised hands and arms, CR (candidate region) search, - transform based shape and GLAC edge features extraction and classification, are applied to find raised hands. The classification is implemented by a hierarchical detector which consists of four SVM classifiers. Experiments show that this method can detect hand-raising gestures well, even for moving persons in crowd.

关键词： Gestures Edge of a figure or solid Human Body Arm spiral arm Arms Shape indoor environment Hand edges Crowding Insulation

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Wheeled Mobile Robot Based on Adaptive Linear Quadratic Gaussian control 29

Wheeled Mobile Robot Based on Adaptive Linear Quadratic Gaus...

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第29届中国控制与决策会议

作者： Yubin Liao Yongsheng Ou Shan Meng Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Shenzhen College of Advanced Technology University of Chinese Academy of Sciences CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Shenzhen University

ISBN: (纸本)9781509046584

To deal with the existing issues of input saturations and uncertain positioning corrupted by Gaussian noises in the tracking control of Wheeled Mobile Robot(WMR),this paper presents a framework which applies the Adaptive Linear Quadratic Gaussian(ALQG) control with Genetic Algorithm based on linear discrete *** work of ALQG includes three ***,to address the problem of input saturations,we consider a linear discrete system as the Lagrangian multiplier and saturation constraint as the inequality constraint,and the linear quadratic controller with the penalty function as the objective function is solved by the interior point ***,in the above implementation of Linear Quadratic Regulator control,the weighting matrix under different conditions may result in different tracking *** address this issue,weighting matrices of different initial poses and reference trajectories are adaptively explored by Genetic Algorithm with control performance indexes as constraint functions,and the optimal weighting matrix is final ***,concerning the uncertainty problem in positioning,the Kalman Filter algorithm with real-time measurement of the disturbed position of the posture filter is applied in real time to obtain more accurate *** ALQG simulation of the WMR is carried out in the MATLAB software platform,and the tracking quality of the ALQG is discussed *** results show that the trajectory tracking controller of wheeled mobile robot based on ALQG can track the target trajectory stably and has good anti-interference abilities.

关键词： Mobile Robot Trajectory Tracking Linear Quadratic Gaussian control

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Hierarchical Policy Optimization for Cooperative Multi-Agent Reinforcement Learning

Hierarchical Policy Optimization for Cooperative Multi-Agent...

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

作者： He, Shunfan Zheng, Ronghao Zhang, Senlin Liu, Meiqin College of Electrical Engineering Zhejiang University Hangzhou310027 China Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Xi'an Jiaotong University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence Xi'an710049 China

ISBN: (纸本)9781665410205

To handle the non-stationarity of the environment and the curse of dimensionality issues in multi-agent reinforcement learning, gathering information through communication is a critical part. Existing frameworks have proposed centralized or distributed structures to deal with the problem. However, they either have problems of robustness or problems of high communication costs. This paper adopts a hierarchical zeroth-order policy optimization (HZOPO) algorithm for cooperative multi-agent reinforcement learning (MARL) problems. The agents are divided into different groups with high-and low-level entities. A hierarchical communication structure is implemented to reach global consensus. It is shown that the HZOPO algorithm can balance both convergence and communication efficiency in cooperative MARL environments. The convergence of the algorithm is also proved. © 2024 IEEE.

关键词： Adversarial machine learning

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Hybrid uniform distribution of particle swarm optimizer

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IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences 2010年第10期E93-A卷 1782-1791页

作者： Zhang, Junqi Tan, Ying Ni, Lina Xie, Chen Tang, Zheng Department of Computer Science and Technology Key Laboratory of Embedded System and Service Computing Ministry of Education Qingdao China Tongji University Shanghai 200092 China Key Laboratory of Machine Perception Ministry of Education Qingdao China Department of Machine Intelligence School of Electronics Engineering and Computer Science Peking University Beijing 100871 China College of Info Sci and Engi Shandong University of Science and Technology Qingdao China Department of Intellectual Information Systems Engineering University of Toyama Toyama-shi 930-8555 Japan

Particle swarm optimizer (PSO) is a stochastic global optimization technique based on a social interaction metaphor. Because of the complexity, dynamics and randomness involved in PSO, it is hard to theoretically analyze the mechanism on which PSO depends. Statistical results have shown that the probability distribution of PSO is a truncated triangle, with uniform probability across the middle that decreases on the sides. The "truncated triangle" is also called the "Maya pyramid" by Kennedy. However, very little is known regarding the sampling distribution of PSO in itself. In this paper, we theoretically analyze the "Maya pyramid" without any assumption and derive its computational formula, which is actually a hybrid uniform distribution that looks like a trapezoid and conforms with the statistical results. Based on the derived density function of the hybrid uniform distribution, the search strategy of PSO is defined and quantified to characterize the mechanism of the search strategy in PSO. In order to show the significance of these definitions based, on the derived hybrid uniform distribution, the comparison between the defined search strategies of the classical, linear decreasing weight based PSO and the canonical constricted PSO suggested by Clerc is illustrated and elaborated. Copyright © 2010 The Institute of Electronics, Information and Communication Engineers.

关键词： Probability distributions

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Remote Sensing Inversion for River Turbidity Estimation Based on Noise Injection and Ensemble Learning

Remote Sensing Inversion for River Turbidity Estimation Base...

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2021 China Automation Congress, CAC 2021

作者： Zhou, Yazhen Shi, Shuang Liu, Hongyan Zhang, Yonghui Gu, Ke Qiao, Junfei Faculty of Information Technology Beijing University of Technology Beijing 100124 China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute

ISBN: (纸本)9781665426473

Turbidity is one main indicator of quality typically used for monitoring water pollution and water eutrophication. The monitoring technology of river water quality can be divided into contact monitoring technology based on physical sensors and non-contact monitoring technology based on remote sensing satellites. The traditional contact monitoring technology has limited monitoring spatial resolution. As a new technology, the remote sensing monitoring technology of the river can conveniently solve the above-mentioned shortcomings and realize the coverage of the whole river basin. However, due to the scarcity of remote sensing data and the measurement errors of remote sensing satellites themselves, learning-based turbidity measurement methods have weak generalization ability and thus are easily prone to produce large deviations. To effectively address such difficulty, a noise injection method is introduced into a river turbidity measurement model based on ensemble learning. To be specific, we randomly generate many noise sets and add them to the remote sensing data to make it closer to the real application scene, and then adopt the ensemble learning model to estimate river turbidity. Experiments validate that the random noise injection strategy can effectively improve the generalization performance of river turbidity measurement. © 2021 IEEE

关键词： Rivers

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Evaluating Image Quality of DIBR-synthesized Views in Texture and Depth Domains

Evaluating Image Quality of DIBR-synthesized Views in Textur...

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2021 China Automation Congress, CAC 2021

作者： Wang, Guangcheng Guo, Nan Liu, Hongyan Zhang, Yonghui Zhou, Yazhen Gu, Ke Faculty of Information Technology Beijing University of Technology Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute Beijing100124 China

ISBN: (纸本)9781665426473

Accurately predicting the quality of depth-image-based-rendering (DIBR) synthesized images is of great significance in promoting DIBR techniques. Recently, Many DIBR-synthesized image quality assessment (IQA) algorithms based on quantifying the distortion existed in texture images have been proposed. However, these methods ignore the damage of DIBR algorithms on the depth structure of DIBR-synthesized images and thus fail to evaluate the visual quality of DIBR-synthesized images accurately. To this end, we present a DIBR-synthesized image quality assessment metric with multi-modal information (i.e. integrating texture and depth information), dubbed as MMI. MMI predicts the quality of DIBR-synthesized images by jointly measuring the texture structure and depth structure of the synthesized image. The design principle of our MMI is that the local geometric distortion, introduced by DIBR techniques in the hole-filling process, destroys the texture structure and the depth structure of DIBR-synthesized images. Thus, we can accurately evaluate DIBR-synthesized image quality by a joint representation of texture structure and depth structure. Experiments show that our MMI is better than the competing state-of-the-art IQA algorithms in predicting DIBR-synthesized image quality. © 2021 IEEE

关键词： Textures

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Distributed Estimation of a Flow Field using Cooperative Underwater Vehicles 63

Distributed Estimation of a Flow Field using Cooperative Und...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： He, Yi Zheng, Ronghao Zhang, Senlin Liu, Meiqin Zhejiang University College of Electrical Engineering Hangzhou310027 China Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Xi'an Jiaotong University The National Key Laboratory of Human-Machine Hybrid Augmented Intelligence Xi'an710049 China

ISBN: (纸本)9798350316339

This paper presents a distributed method of cooperative flow field estimation using a group of underwater vehicles in GPS-denied environments without directly measuring the ambient flow velocity. We consider that the vehicle can measure the relative positions of its neighbors and the absolute position when it surfaces. By formulating the measurements into the relative and absolute motion-integration error constraints, the flow field estimation problem is converted into an inverse problem that solves a determined system of nonlinear equations in a distributed way. We then propose a distributed consensus algorithm to solve the above equations, in which each vehicle first shares local flow estimate with its neighbors, and then updates the estimate using local constraints. The convergence of the proposed algorithm is strictly guaranteed, and simulations are provided to validate its effectiveness. © 2024 IEEE.

关键词： Inverse problems

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