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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Guo, Jian Huo, Xiaojie Guo, Shuxiang Xu, Jigang Tianjin University of Technology Binshui Xidao Extension 391 Tianjin Key Laboratory for Control Theory Applications In Complicated Systems and Intelligent Robot Laboratory Faculty of Engineering Tianjin300384 China Unit68709 Qinghai Haidong810700 China

ISBN: (纸本)9781728164151

With the development and progress of science and technology, the requirement of intelligent algorithm performance in the field of path planning is constantly improved. It is very important to improve the performance of intelligent algorithm and apply it in the field of path planning. In order to overcome the problem that ant colony algorithm tends to fall into local optimal in the early stage and converge slowly in the late stage. This paper proposed an ant colony algorithm based on adaptive pheromone updating strategy and enhanced negative feedback mechanism. The simulation results show that the improved ant colony algorithm is superior to the traditional ant colony algorithm and solves the problem of insufficient convergence in the early stage and low convergence in the late stage. Finally, the algorithm is tested by spherical robot. The experimental results show that the improved ant colony algorithm overcomes the shortcomings of traditional algorithms and verifies the effectiveness and convergence of the algorithm. © 2020 IEEE.

关键词： Motion planning

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A CNN-LSTM Hybrid Model for Ankle Joint Motion Recognition Method Based on sEMG

A CNN-LSTM Hybrid Model for Ankle Joint Motion Recognition M...

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Hao-Ran Cheng Guang-Zhong Cao Cai-Hong Li Aibin Zhu Xiaodong Zhang Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robots Shenzhen Key Laboratory of Electromagnetic Control College of Mechatronics and Control Engineering Shenzhen University Shenzhen China Institute of Robotics & Intelligent Systems Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots Xi'an China

ISBN: (数字)9781728157153

ISBN: (纸本)9781728157160

A CNN-LSTM hybrid model for ankle joint motion recognition based on surface electromyography (sEMG) signals is proposed in this paper. The traditional recognition method is to manually extract the features from sEMG signals and then use machine learning method to train the model, which relies on prior knowledge and requires a lot of time to test and select good features to obtain high classification accuracy. In this paper, the CNN-LSTM hybrid model is used to identify four ankle joint movements (dorsiflexion, plantar flexion, foot varus and foot eversion). The hybrid model consists of two CNN layers and three LSTM layers. CNN can learn to automatically extract features and LSTM is able to capture long-term correlations of sEMG data. The experiment results show that the proposed model is effective and accurate, thus providing a basis for the subsequent research.

关键词： Feature extraction Convolution Machine learning Logic gates Neurons Kernel Robots

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Learning-Based Model Predictive control for Vehicles with Modeling Bias 42

Learning-Based Model Predictive Control for Vehicles with Mo...

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42nd Chinese control Conference, CCC 2023

作者： Qi, Xudong Zhang, Libin Wang, Ping Han, Yu Lin, Wanquan School of Electronics and Control Engineering Chang'An University Xi'an710064 China School of Intelligent Systems Engineering Sun Yat-Sen University Shenzhen518107 China Guangdong Key Laboratory of Fire Science and Intelligent Emergency Technology Guangzhou528406 China

ISBN: (纸本)9789887581543

The dynamic uncertainty system has modeling bias, which has led to an increasing interest in learning-based model-driven control technology. In order to integrate the advantages of self-exploration of reinforcement learning (RL) and high robustness of model predictive control (MPC), we propose a learning-based model predictive control (LMPC) method. This algorithm is a method that can find the optimal control strategy under the guidance of simplified model and fuzzy cost function. The results show that taking vehicle motion control as an example. By adjusting the variable horizon, the vehicle model built can quickly and effectively achieve the control objectives. Compared with DDQN, LMPC reduces the disorder enumeration of RL, accelerates the optimization process of the control system to the target, and makes the exploration process more stable. Compared with MPC, it solves the problem that the control accuracy of the control system is not high and the model and parameters cannot be adjusted adaptively under the simplified modeling. © 2023 Technical Committee on control theory, Chinese Association of Automation.

关键词： Model predictive control

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Displacement-Based Formation control with Measurement Noises

Displacement-Based Formation Control with Measurement Noises

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IEEE Conference on Decision and control

作者： Weiqiang Chen Liangming Chen Jie Mei Hongwei Zhang School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen China Shenzhen Key Laboratory of Control Theory and Intelligent Systems Center for Control Science and Technology Southern University of Science and Technology Shenzhen China

Multi-agent formations have many practical applications. Measurement noises are inevitable in multi-agent formations, in which, however, the existing results mainly focus on special types of noises, and the analytical discussion on the effect of general noises is challenging and remains open. This motivates us to study the effect of stochastic measurement noises on displacement-based multi-agent formations, which are described by a general form of stochastic processes with finite second-order moments. First, for the case of unbiased measurement noises, a sufficient and necessary condition is derived for the existence of solutions in the stochastic dynamics of multi-agent formations. Then, several statistical features and convergence of formation errors are analyzed. In particular, for the case of unbiased measurement noises described by zero-mean wide-sense stationary processes, an upper bound on the mean square convergence of formation errors is obtained. Finally, we demonstrate the effectiveness of our theoretical results through a simulation example.

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Multi-Resolution Planar Region Extraction for Uneven Terrains

Multi-Resolution Planar Region Extraction for Uneven Terrain...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yinghan Sun Linfang Zheng Hua Chen Wei Zhang Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China School of Computer Science University of Birmingham UK

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper studies the problem of extracting planar regions in uneven terrains from unordered point cloud measurements. Such a problem is critical in various robotic applications such as robotic perceptive locomotion. While existing approaches have shown promising results in effectively extracting planar regions from the environment, they often suffer from issues such as low computational efficiency or loss of resolution. To address these issues, we propose a multi-resolution planar region extraction strategy in this paper that balances the accuracy in boundaries and computational efficiency. Our method begins with a pointwise classification preprocessing module, which categorizes all sampled points according to their local geometric properties to facilitate multi-resolution segmentation. Subsequently, we arrange the categorized points using an octree, followed by an in-depth analysis of nodes to finish multi-resolution plane segmentation. The efficiency and robustness of the proposed approach are verified via synthetic and real-world experiments, demonstrating our method’s ability to generalize effectively across various uneven terrains while maintaining real-time performance, achieving frame rates exceeding 35 FPS.

关键词： Point cloud compression Deep learning Accuracy Octrees Noise Robustness Real-time systems

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Implementation and Application of Solvers for Simulation and Execution of control Algorithms in NCSLab

Implementation and Application of Solvers for Simulation and...

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International Conference on Electronic Engineering and Informatics (EEI)

作者： Jiuzheng Su Zhongcheng Lei Wenshan Hu Guo-Ping Liu Department of Artificial Intelligence and Automation Wuhan University Wuhan China Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

In order to solve the problems of high dependency and low flexibility caused by calling three-party services during simulation and experiments, this paper uses the NCSLab (Networked control System laboratory) as an application platform to implement the functions of multiple ordinary differential equation solvers, which are used for real-time simulation and experimentation of control algorithm. This paper mainly integrates the common ordinary differential equation solving methods and NCSLab platform, and verifies the support of NCSLab platform for different solving methods through the actual simulation process.

关键词： Networked control systems Computational modeling Ordinary differential equations Real-time systems Computational efficiency Informatics

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The Shortest Path Algorithm Based on Geometric Symmetry for Low Earth Orbit Satellite Network

The Shortest Path Algorithm Based on Geometric Symmetry for ...

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Information Communication Technologies Conference (ICTC)

作者： Benchu Zhang Zaiyue Yang School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China Shenzhen Key Laboratory of Control Theory and Intelligent Systems and the School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350373523

ISBN: (纸本)9798350373530

Since the Low Earth Orbit (LEO) satellite communication system has the advantages of low latency, global coverage, and rapid reconstruction, it has become the main networking method of satellite networks [1]. Routing is the basis for realizing satellite communications. Because the complexity of the shortest path algorithm basically determines the computational complexity of the routing algorithm, the shortest path algorithm is the core of the routing problem. This paper attempts to use the laws of LEO satellite network topology to calculate the shortest path between the source satellite and the destination satellite. First, we derive the function of inter-satellite link (ISL) length with time and establish the geometric model of the satellite network. Then, on the basis of this model, we establish the shortest path algorithm between source-destination pairs (SD pairs) - the symmetric geometry algorithm (SGA). In addition, in order to ensure the optimality of the path, we extend the applicable scene of the model from the two-dimensional plane to the three-dimensional sphere. The simulation test results show that compared with the traditional Dijkstra’s algorithm, SGA can greatly improve the calculation speed of the shortest path while ensuring the optimality of the path.

关键词： Geometry Solid modeling Satellites Network topology Geometric modeling Low earth orbit satellites Routing

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Design of wireless mobile environment monitoring system based on spherical amphibious robots 15

Design of wireless mobile environment monitoring system base...

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15th IEEE International Conference on Mechatronics and Automation, ICMA 2018

作者： Guo, Shuxiang Yang, Xujie Guo, Jian Li, Chunying Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems and Biomedical Robot Laboratory Tianjin University of Technology Binshui Xidao Tianjin391 China Intelligent Mechanical Systems Engineering Department Faculty of Engineering Kagawa University 2217-20 Hayashi-cho Takamatsu761-0396 Japan

ISBN: (纸本)9781538660720

A wireless mobile environmental monitoring system based on spherical amphibious robots is proposed in this paper, which is used to monitor environmental data in *** control interface is designed by using labVIEW to display the collected environmental *** XBee module is used to realize the wireless communication between robot and PC. The robot is equipped with temperature and humidity sensors, pressure sensors and high-definition cameras to collect environmental information. An adaptive weighted fusion algorithm is proposed for deal with the multi source data collected by multiple robots and improve the accuracy of *** this paper, the underwater kinematic model of amphibious robot is established, and the proportional-integral-derivative(PID) controller is designed to control the depth of spherical amphibious robot. The simulation and experimental results verified the effectiveness of the system. © 2018 IEEE.

关键词： Robots

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Rethinking Distribution Alignment for Inter-class Fairness 1

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1st International Conference on Artificial Intelligence Security and Privacy, AIS and P 2023

作者： Ye, Jinhuang Wu, Jiawei Li, Zuoyong Zheng, Xianghan College of Computer and Big Data Fuzhou University Fuzhou350108 China School of Intelligent Systems Engineering Sun Yat-sen University Shenzhen518107 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China

ISBN: (数字)9789819997886

ISBN: (纸本)9789819997879

Semi-supervised learning (SSL) is a successful paradigm that can use unlabelled data to alleviate the labelling cost problem in supervised learning. However, the excellent performance brought by SSL does not transfer well to the task of class imbalance. The reason is that the class bias of pseudo-labelling further misleads the decision boundary. To solve this problem, we propose a new plug-and-play approach to handle the class imbalance problem based on a theoretical extension and analysis of distribution alignment. The method, called Basis Transformation Based Distribution Alignment (BTDA), efficiently aligns class distributions while taking into account inter-class *** implements the basis transformation through a learnable transfer matrix, thereby reducing the performance loss caused by pseudo-labelling biases. Extensive experiments show that our proposed BTDA approach can significantly improve performance in class imbalance tasks in terms of both accuracy and recall metrics when integrated with advanced SSL algorithms. Although the idea of BTDA is not complex, it can show advanced performance on datasets such as CIFAR and SVHN. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Image classification

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Multi-Resolution Planar Region Extraction for Uneven Terrains

arXiv

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arXiv 2023年

作者： Sun, Yinghan Zheng, Linfang Chen, Hua Zhang, Wei Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China School of Computer Science University of Birmingham United Kingdom

关键词： Computational efficiency

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