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IEEE International Conference on Networking, Sensing and control

作者： Boyu Li Weimin Wu State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9798350365221

ISBN: (纸本)9798350365238

With the increasing prevalence of automated guided vehicles (AGV s) in industry, the AG V dispatching has emerged as a research hotspot. Recently, matrix manufacturing systems (MMS) have been favored for their suitability in mass-customized production. However, fluctuating and diverse transport demands in MMS pose challenges for effective AGV scheduling. This paper investigates a multi-AGV dispatching problem (AGVDP) in MMS, involving time-constrained pick-up and delivery tasks. A mixed-integer linear programming model is developed to minimize total transportation costs, including travel distance, early arrival time, and utilized AGV s. To achieve this, an effective adaptive large neighborhood search algorithm (ALNS) is proposed. In ALNS, a scope-based nearest neighbor heuristic is introduced for initial construction. Diverse problem-specific operators are designed to generate large neighborhoods. To enhance ALNS's robustness to instance variations, an adaptive simulated annealing acceptance criterion is proposed. Computational experiments using a well-established benchmark validate the superiority of the proposed ALNS.

关键词： Adaptation models Sensitivity Transportation Simulated annealing Search problems Dispatching Sensors Time factors Tuning Manufacturing systems

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Research on Optimization Seeking Method of Transmission Efficiency of Orbital Inspection Robot Based on DWPT System

Research on Optimization Seeking Method of Transmission Effi...

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IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific)

作者： Youcheng Chen Zhitao Liu Xuchi Xue Hongye Su State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9798331529277

ISBN: (纸本)9798331529307

In wireless power transmission system, due to the changes of coupling coefficient, load impedance and other factors, it destroys the system constant voltage, constant power output and transmission efficiency optimal working condition. Therefore, this paper proposes an optimization seeking method for the maximum transmission efficiency of the DWPT system of an orbital inspection robot with constant voltage and constant power output. Firstly, the LCC-S topology mathematical model with additional PI control circuit and the convex optimization model of transmission efficiency are established, and the gradient descent algorithm is used to iteratively search for the maximum value of transmission efficiency when the orbital coupling coefficient changes. Then, based on the mutual inductance model between coils, the coupling coefficients are converted into coil inductance parameters L 1 and L 2 , and the coil self-inductance is utilized for matching regulation to keep the transmission efficiency at the optimal value. Finally, in order to further optimize and predict the transmission efficiency, the fitting effects of the four fitting curves of the transmission efficiency are observed by the coefficient of determination and the residual paradigm, and the optimal fitting curves are used to calculate the maximum and average transmission efficiency, which reduces the system transmission loss and improves the charging efficiency.

关键词： Coils Couplings Inductance Fitting Inspection Orbits Mathematical models Integrated circuit modeling Optimization Robots

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Whole-body Dynamic Collision Avoidance with Time-varying control Barrier Functions

Whole-body Dynamic Collision Avoidance with Time-varying Con...

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Chinese control and Decision Conference, CCDC

作者： Jihao Huang Xuemin Chi Zhitao Liu Hongye Su State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

Recently, there has been increasing attention in robot research towards the whole-body collision avoidance. In this paper, we propose a safety-critical controller that utilizes time-varying control barrier functions (time varying CBFs) constructed by Robo-centric Euclidean Signed Distance Field (RC-ESDF) to achieve dynamic collision avoidance. The RCESDF is constructed in the robot body frame and solely relies on the robot’s shape, eliminating the need for real-time updates to save computational resources. Additionally, we design two control Lyapunov functions (CLFs) to ensure that the robot can reach its destination. To enable real-time application, our safety-critical controller which incorporates CLFs and CBFs as constraints is formulated as a quadratic program (QP) optimization problem. We conducted numerical simulations on two different dynamics of an L-shaped robot to verify the effectiveness of our proposed approach.

关键词： Silver Navigation Shape Numerical simulation Real-time systems Trajectory Collision avoidance

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A Monocular Biological Simultaneous Localization and Mapping Method Based on a Bionic Vision Model

A Monocular Biological Simultaneous Localization and Mapping...

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2023 International Conference on Frontiers of Robotics and Software Engineering, FRSE 2023

作者： Guo, Sitong Zhang, Yu Zhejiang University Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou China

ISBN: (纸本)9798350301113

Animals can navigate robustly through large unknown environments, utilizing inaccurate sensor and egomotion cues. Inspired by the mechanism of the human visual system, this paper presents a biological simultaneous localization and mapping (SLAM) system based on a monocular vision sensor to perform navigation tasks in complex environments. Specifically, our contributions are two folds: an improved monocular visual odometry with a scale recovery algorithm to calibrate the estimated robot pose, and a bionic vision model based on image enhancement algorithm and feature extraction approach to detect closed-loop. Experiments on public datasets demonstrate that our proposed method performs competitively in illumination-varying scenarios indoors and outdoors, which achieve a trade-off to maintain performances in terms of accuracy, execution time, and robustness. © 2023 IEEE.

关键词： Vision

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SOMTP: Self-Supervised Learning-Based Optimizer for MPC-Based Safe Trajectory Planning Problems in Robotics

arXiv

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arXiv 2024年

作者： Liu, Yifan Wang, You Li, Guang State Key Laboratory of Industrial Control Technology Institute of Cyber Systems and Control Zhejiang University Hangzhou310027 China

Model Predictive control (MPC)-based trajectory planning has been widely used in robotics, and incorporating control Barrier Function (CBF) constraints into MPC can greatly improve its obstacle avoidance efficiency. Unfortunately, traditional optimizers are resource-consuming and slow to solve such non-convex constrained optimization problems (COPs) while learning-based methods struggle to satisfy the non-convex constraints. In this paper, we propose SOMTP algorithm, a self-supervised learning-based optimizer for CBF-MPC trajectory planning. Specifically, first, SOMTP employs problem transcription to satisfy most of the constraints. Then the differentiable SLPG correction is proposed to move the solution closer to the safe set and is then converted as the guide policy in the following training process. After that, inspired by the Augmented Lagrangian Method (ALM), our training algorithm integrated with guide policy constraints is proposed to enable the optimizer network to converge to a feasible solution. Finally, experiments show that the proposed algorithm has better feasibility than other learning-based methods and can provide solutions much faster than traditional optimizers with similar optimality. Copyright © 2024, The Authors. All rights reserved.

关键词： Model predictive control

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Few Shot Object Detection Based on Graph Attention Network 4

Few Shot Object Detection Based on Graph Attention Network

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4th IEEE International Conference on Pattern Recognition and Machine Learning, PRML 2023

作者： Ding, Rou Zhang, Yu Zhejiang University of Control Science and Engineering State Key Laboratory of Industrial Control Technology Zhejiang China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province Zhejiang China

ISBN: (纸本)9798350324303

Few shot object detection is a challenging task in computer vision, as it involves detecting objects from a small number of examples. This makes it difficult for traditional object detection methods to generalize well to new classes or scenes. In this paper, we propose a siamese neural network model that utilizes the power of Faster RCNN for few shot object detection. The network takes in support and query datasets and extracts both support and query features. To supplement category information between various support features, we use Pearson similarity to enhance the features and extract support prototypes. We propose a graph attention network that can perform association matching between support prototype and proposals. Through this network, we facilitate information exchange between support features and query features, which helps to supplement the information of query images. We divide the training process into two stages. In the first stage, we use a large amount of basic category data to train the basic detection ability. In the second stage, we further train our model on few shot novel class and base class mixed datasets to improve its generalization performance. Experimental results on the public Pascal VOC dataset demonstrate that our proposed method achieves state-of-The-Art few shot object detection performance. © 2023 IEEE.

关键词： Object detection

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An activated variable parameter gradient‐based neural network for time‐variant constrained quadratic programming and its applications

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CAAI Transactions on Intelligence technology 2023年第3期8卷 670-679页

作者： Guancheng Wang Zhihao Hao Haisheng Li Bob Zhang PAMI Research Group Department of Computer and Information ScienceUniversity of MacaoTaipaMacaoChina China Industrial Control Systems Cyber Emergency Response Team BeijingChina Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business UniversityBeijingChina

This study proposes a novel gradient‐based neural network model with an activated variable parameter,named as the activated variable parameter gradient‐based neural network(AVPGNN)model,to solve time‐varying constrained quadratic programming(TVCQP)*** with the existing models,the AVPGNN model has the following advantages:(1)avoids the matrix inverse,which can significantly reduce the computing complexity;(2)introduces the time‐derivative of the time‐varying param-eters in the TVCQP problem by adding an activated variable parameter,enabling the AVPGNN model to achieve a predictive calculation that achieves zero residual error in theory;(3)adopts the activation function to accelerate the convergence *** solve the TVCQP problem with the AVPGNN model,the TVCQP problem is transformed into a non‐linear equation with a non‐linear compensation problem function based on the Karush Kuhn Tucker ***,a variable parameter with an activation function is employed to design the AVPGNN *** accuracy and convergence rate of the AVPGNN model are rigorously analysed in ***,numerical experiments are also executed to demonstrate the effectiveness and superiority of the proposed ***,to explore the feasibility of the AVPGNN model,appli-cations to the motion planning of a robotic manipulator and the portfolio selection of marketed securities are illustrated.

关键词： computational intelligence mathematics computing optimisation

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Application Design of Virtual Immersion Command Information System 9

Application Design of Virtual Immersion Command Information ...

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9th International Conference on Big Data and Information Analytics, BigDIA 2023

作者： Liu, Renjie Chen, Hongli Wang, Mingyang Zhu, Jian Zhang, Zhenqian Zhang, Ming Beijing Institute of Control and Electronic Technology Key Laboratory of Information System and Technology Beijing China China Industrial Control Systems Cyber Emergency Response Team Laboratory of Artificial Intelligence Integration Development and Security Application Beijing China

ISBN: (纸本)9798350330076

Based on the existing resources of general command information system, the virtually immersive display system is constructed. In this paper, the application design of virtual and augmented reality display system was discussed. The main contents included the overall system design, business requirements, application design of virtual reality (VR) and augmented reality (AR) table display system, expected results, and equipment selection. The deployment and application of VR and AR display system were introduced. Therefore, the hardware selection of VR and AR were HTC Vive and XLOOG X200 products, respectively. The Unreal Engine 4 was selected as the software development platform. This solution meets the current immersive display requirements. The system integrates VR and AR display application capabilities and can fully serve the command and control requirements in the future virtual field. © 2023 IEEE.

关键词： Virtual reality

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Obstacle Based Fast Marching Tree for Global Motion Planning 48

Obstacle Based Fast Marching Tree for Global Motion Planning

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48th Annual Conference of the IEEE industrial Electronics Society, IECON 2022

作者： Hou, Jiale Liu, Zhitao Su, Hongye Zhejiang University Polytechnic Institute Hangzhou China Zhejiang University Institute of Cyber-Systems and Control State Key Laboratory of Industrial Control Technology Hangzhou China

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

In this paper we introduce a novel method to improve the general performance of fast marching tree for collision-free path planning called obstacle-based fast marching tree. Our proposed OB-FMT∗ samples the map in discussion initially to obtain the vertexes of all obstacles and connect those vertexes to build a collision-free roadmap, an A*algorithm is adopted to find an optimal path in the built roadmap. Then multiple prolate hyper spheroids with focuses on vertexes of optimal path are established to limit the sampling range. Within the limited sampling point set, we utilize FMT∗ to find optimal solution with high efficiency. Theoretical analyses are given to prove the probabilistic completeness and computational complexity of our proposed method. Experiments in multiple scenarios show that our algorithm has a better performance comparing with other existing algorithms including RRT*, FMT*, Informed RRT*. © 2022 IEEE.

关键词： Motion planning

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Hetero-Source Sensors Localization Based on High-Precision Map

Hetero-Source Sensors Localization Based on High-Precision ...

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Chinese Intelligent Automation Conference, CIAC 2023

作者： Cui, Zhuofan Tao, Junyi He, Bin Zhang, Yu State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province Hangzhou China

ISBN: (纸本)9789819961863

High-precision maps and localization techniques are important modules in robot systems. However, the existing simultaneous localization and mapping methods using the same sensors in both localization and mapping tasks suffers from high costs and inflexibility. Therefore, the method of implementing a low-cost visual sensor to achieve indoor localization with the pre-obtained high-precision point cloud maps is proposed in this paper. To find a similar area represented by point cloud of the maps and the sensors, a localization strategy based on ICP for point cloud matching is completed on the premise of giving a rough initial pose. Meanwhile, visual odometry is integrated into the localization framework to conquer the localization failure caused by repeated point cloud features in indoor environments. The sub-meter level localization accuracy in the indoor building environment is achieved in the experiments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Mapping

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