检索结果-内蒙古大学图书馆

18th IEEE International Conference on Networking, Sensing and control, ICNSC 2021

作者： Niu, Haoyi Xing, Zichao Wang, Xingkai Wu, Weimin Zhang, Tao Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Hangzhou China

ISBN: (纸本)9781665440486

This paper studies a flexible flow-shop scheduling problem with limited resources (FFSP-LR) which is based on an actual air-conditioning production line in an intelligent manufacturing system. It extends the classical flexible flow-shop scheduling problem by considering practical constraints of the number of the AGVs (automated guided vehicles) on the transportation resources. The problem aims to determine the optimal scheduling results that minimizes the idle waiting time and pick-up waiting time of the workstations. To solve this problem, a pre-waiting scheduling model (PWSM) is proposed by taking into account the advance waiting time of AGVs. The experimental results show that the proposed PWSM is able to reduce idle waiting time and pick-up waiting time up to 425.01 and 414.25 comparing to traditional FCFS (First Come First Serve) strategy respectively. Correspondingly, these two types of time could be saved up to 87.01% and 98.57%. Finally, the overall efficiency of the intelligent manufacturing system is improved since the PWSM is able to effectively reduce the idle waiting time and pick-up waiting time of the workstations under the condition of limited transportation resources. © 2021 IEEE.

关键词： Air conditioning

来源：评论

学校读者我要写书评

暂无评论

Reinforcement Learning for Adaptive Planner Parameter Tuning: A Perspective on Hierarchical Architecture

arXiv

引用

arXiv 2025年

作者： Lu, Wangtao Wei, Yufei Xu, Jiadong Jia, Wenhao Li, Liang Xiong, Rong Wang, Yue State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China College of Information and Engineering Zhejiang University of Technology Hangzhou310023 China

Automatic parameter tuning methods for planning algorithms, which integrate pipeline approaches with learning-based techniques, are regarded as promising due to their stability and capability to handle highly constrained environments. While existing parameter tuning methods have demonstrated considerable success, further performance improvements require a more structured approach. In this paper, we propose a hierarchical architecture for reinforcement learning-based parameter tuning. The architecture introduces a hierarchical structure with low-frequency parameter tuning, mid-frequency planning, and high-frequency control, enabling concurrent enhancement of both upper-layer parameter tuning and lower-layer control through iterative training. Experimental evaluations in both simulated and real-world environments show that our method surpasses existing parameter tuning approaches. Furthermore, our approach achieves first place in the Benchmark for Autonomous Robot Navigation (BARN) Challenge. Copyright © 2025, The Authors. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

A Decision-support Framework for Port Container Stowage Plan 18

A Decision-support Framework for Port Container Stowage Plan

引用

18th IEEE International Conference on Networking, Sensing and control, ICNSC 2021

作者： Wang, Shuo Zhang, Tao Xing, Zichao Wu, Weimin Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Hangzhou China

ISBN: (纸本)9781665440486

With the development of international trade, container transportation increases rapidly. Loading large quantities of containers requires efficient port operations and an efficient container stowage plan (CSP). A CSP is the placement of containers onto the shipping plan slots, which should decrease loading cost and keep the ship stability. The yard operational efficiency, ship stability, and operational safety are the major factors that should be considered in port loading and unloading. Since, factors are related to others, to generate a CSP is proven to be NP-complete. This paper proposes a decision-support framework for determining a shipment plan, which is to achieve the optimal shipment objects by a planning model. The experimental results show that the proposed framework can improve the operating efficiency of the storage yard while keeping the ship's stability and reducing the dangerous loading scenes. © 2021 IEEE.

关键词： Containers

来源：评论

学校读者我要写书评

暂无评论

Improved Hybrid Gaussian Process Regression Model for state-of-Health Estimation of Li-ion Batteries

Improved Hybrid Gaussian Process Regression Model for State-...

引用

Chinese Automation Congress (CAC)

作者： Tao An Zhitao Liu Chizhou Yan Ke Xu Hongye Su State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Wanxiang A123 Systems Corp. Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Accurate state-of-health (SOH) estimation con-tributes to the healthy and stable operation of the Li-ion batteries. This paper proposes an improved hybrid Gaussian process regression (GPR) method incorporating physical information for the high-accuracy estimation of battery SOH. The estimation process considers the effects of temperature, discharge rate, and depth of discharge (DOD) on the battery health, and the relevant features of the electrode degradation process are extracted for battery SOH estimation. The kernel function of GPR comprehensively considers the mechanical characteristics of battery degradation and can effectively track the battery degra-dation process. The validation experiments were conducted on the A123 LFP/Graphite battery dataset. Sufficient comparative experiments have validated the accuracy and robustness of the proposed method.

关键词： Lithium-ion batteries Electrodes Degradation Accuracy Estimation Gaussian processes Feature extraction Robustness Batteries Kernel

来源：评论

学校读者我要写书评

暂无评论

Multi-agent trajectory prediction based on graph neural network

Multi-agent trajectory prediction based on graph neural netw...

引用

2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

作者： Du, Haozhe Chen, Zhike Wang, Yufeng Huang, Zheyuan Wang, Yunkai Xiong, Rong Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Hangzhou China

ISBN: (纸本)9781665436786

Many tasks have demand on precise predictions of agents or moving objects. Previous prediction methods usually only focus on the kinematic model of moving objects or the environment. However, the target tasks of agents may influence the prediction of agents in great sense, especially in tasks of confrontation. Therefore traditional methods cannot work well in such scenes. In this paper, we propose a heterogeneous graph neural network method to deal with the multi-agent trajectory prediction problem. Our method can aggregate and pass messages representing environment and also agents' tasks due to the elaborate design of graph neural network structure. We validate our method on the Robocup Small Size League simulation platform which focuses on multi-agent coordination and confrontation in the form of soccer games. After making our own ZJUNlictSSL dataset, we predict the position of all robots on the pitch of certain time gaps based on the limited information we get from vision. The results prove that our method is of high prediction accuracy and low prediction error compared with conventional kinematic motion methods. Code is available here. © 2021 IEEE.

关键词： Simulation platform

来源：评论

学校读者我要写书评

暂无评论

A Novel Searching Method of Fringe Blocks for AGV Deadlock Avoidance 18

A Novel Searching Method of Fringe Blocks for AGV Deadlock A...

引用

18th IEEE International Conference on Networking, Sensing and control, ICNSC 2021

作者： Chen, Xinyu Zhang, Tingqi Wu, Weimin Hu, Ruifen Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Hangzhou China

ISBN: (纸本)9781665440486

With the increasing development of automated logistics systems, automated guided vehicles (AGVs) have been gradually deployed in various logistics systems. AGVs are mainly used to transport materials and products, which promote the efficiency greatly and provide profound flexibility and safety. The strategy to prevent AGVs from forming deadlocks is one of the fundamental and vital issues in applications. In this paper, a common type of deadlock that usually occurs in warehouses and a typical attribute of map called fringe blocks are studied thoroughly. To solve the deadlock, it's crucial to identify fringe blocks. We first use traditional depth first search algorithm (DFS) to find out all the fringe blocks in the map. Then, confronted with the huge time complexity, we combine the DFS procedure with a high-efficiency trimming method. Finally, we run a simulation and make a comparison of both methods. The simulation results have shown that the proposed strategy will reduce computational time significantly without making false judgements. © 2021 IEEE.

关键词： Efficiency

来源：评论

学校读者我要写书评

暂无评论

Research on Container Slot Planning for Coordinated Operation of Quay Cranes and Yard Cranes 18

Research on Container Slot Planning for Coordinated Operatio...

引用

18th IEEE International Conference on Networking, Sensing and control, ICNSC 2021

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

ISBN: (纸本)9781665440486

Given ship per-stowage plan and yard stacking status, this paper presents a method on container slot planning for coordinated operation of quay cranes (QC) and yard cranes (YC). A multi-objective programming model is established with the goal of maximizing the turnover rate of container terminal. Then, a heuristic construction algorithm is designed to obtain an initial stowage plan. In addition, an annealing genetic algorithm is proposed to optimize this initial solution. A wide variety of numerical experiments demonstrated that stowage plans made by this method are useful and applicable in practice. © 2021 IEEE.

关键词： Containers

来源：评论

学校读者我要写书评

暂无评论

A Two-Stage Congestion-Aware Routing Method for Automated Guided Vehicles in Warehouses 18

A Two-Stage Congestion-Aware Routing Method for Automated Gu...

引用

18th IEEE International Conference on Networking, Sensing and control, ICNSC 2021

作者： Chen, Xinyu Feng, Ligen Wang, Xingkai Wu, Weimin Hu, Ruifen Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Hangzhou China

ISBN: (纸本)9781665440486

With multi-AGV (automated guided vehicle) systems gradually employed in modern warehouses, the research on how to coordinate AGVs in an efficient way has attracted more scholars than ever. As the size of AGVs grows over time, the possibility of traffic congestion is increasing rapidly, especially in a limited space. Therefore, the congestion-aware routing method is one of the most vital and fundamental topics in multi-AGV control research. In this paper, a two-stage congestion-minimizing routing method is presented. The proposed method not only plans paths that avoid congested areas, but also changes paths in real time to cope with the volatile traffic situations. An experiment is carried out to test the effectiveness and efficiency of the proposed method, and the results are highly promising in terms of alleviating traffic congestion. © 2021 IEEE.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

Collaborative recognition of feasible region with aerial and ground robots through DPCN

Collaborative recognition of feasible region with aerial and...

引用

2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

作者： Li, Yunshuang Huang, Zheyuan Chen, Zexi Wang, Yue Xiong, Rong Institute of Cyber-Systems and Control Zhejiang University State Key Laboratory of Industrial Control Technology Zhejiang China

ISBN: (纸本)9781665436786

Ground robots always get collision in that only if they get close to the obstacles, can they sense the danger and take actions, which is usually too late to avoid the crash, causing severe damage to the robots. To address this issue, we present a collaborative system with aerial and ground robots to gain precise recognition of feasible region. Taking the aerial robots' advantages of having large scale variance of view points of the same route which the ground robots is on, the collaboration work provides global information of road segmentation for the ground robot, thus enabling it to obtain feasible region and adjust its pose ahead of time. Under normal circumstance, the transformation between these two devices can be obtained by GPS yet with much error, directly causing inferior influence on recognition of feasible region. Thereby, we utilize the state-of-the-art research achievements in matching heterogeneous sensor measurements called deep phase correlation network(DPCN), which has excellent performance on heterogeneous mapping, to refine the transformation. The network is light-weighted and promising for better generalization. We use Aero-Ground dataset which consists of heterogeneous sensor images and aerial road segmentation images. The results show that our collaborative system has great accuracy, speed and stability. © 2021 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Multi-stage decision-making skill learning for soccer robot

Multi-stage decision-making skill learning for soccer robot

引用

2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

作者： Chen, Zhike He, Zhiye Du, Haozhe Han, Chengrui Wang, Yunkai Chen, Zexi Xiong, Rong Institute of Cyber-Systems and Control Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou China

ISBN: (纸本)9781665436786

The application scenarios of robots are becoming more and more complex, leading to higher and higher demand on skills for robots. This paper proposes a method to learn complex skill by decomposing it into basic skills, then train them respectively as well as combination into a whole, where reinforcement learning are used both in basic skill learning and in the integration. The method proposed is validated on the RoboCup small soccer robot platform via the skill of chasing and shooting ball and tested in both simulation environment and real world. It is verified our method has achieved a higher success rate comparing with traditional methods. Code is available here. © 2021 IEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：