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IEEE International Conference on Networking, Sensing and control

作者： Zhenrui Rong Weimin Wu Xingkai Wang Xiaojie Jin State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (纸本)9781665440493

With the rapid development of global container business, there are higher requirements for the operation efficiency of container terminals. The vehicle dispatching system is an important link in the operation of container terminal. The yard environment of container terminal is very complex, and the traditional global optimization model based on time estimation is no longer suitable to deal with the vehicle dispatching problem in the scene of dock. This paper proposes a real-time vehicle scheduling strategy for container terminals. Firstly, a buffer vehicle pool is designed to balance the efficiency of each quay crane (QC). Secondly, the wider neighborhood simulated annealing algorithm (WNSA) is presented to find the optimal matching result of each round of calculation. The experimental results show that the proposed strategy in this paper is able to improve the operation efficiency of the QCs and reduce the vehicle cost in the container terminal.

关键词： Cranes Estimation Simulated annealing Containers Real-time systems Scheduling Dispatching

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Extraction of main factors affecting muscle fatigue in lower-limb rehabilitation 41

Extraction of main factors affecting muscle fatigue in lower...

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第41届中国控制会议

作者： Tiecheng Liu Rennong Wang Jinhua She Juan Zhao Hiroshi Hashimoto Daisuke Chugo Graduate School of Engineering Tokyo University of Technology School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Industrial Technology Advanced Institute of Industrial Technology Graduate School of Science and Technology Kwansei Gakuin University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This study extracted the main factors from a questionnaire,measurement results,and the analysis of sEMG signals to establish a method of evaluating muscle *** measured factors(rating of perceived exertion,heart rate,mileage) and five factors obtained from the analysis of sEMG signals(root mean square,mean absolute value,variance,times of zero crossing,median frequency) were *** the F-test,the correlation analysis,and the principal component analysis,we finally extracted six factors as the main factors that have a big influence on muscle fatigue.

关键词： correlation analysis F-test lower-limb rehabilitation muscle fatigue principal component analysis rehabilitation statistical analysis surface electromyography(sEMG)

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A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 812-833页

作者： Xinlei Yi Shengjun Zhang Tao Yang Tianyou Chai Karl Henrik Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technologyand also affiliated with the Digital FuturesStockholm 10044Sweden Department of Electrical Engineering University of North TexasDentonTX 76203 USA IEEE State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China

The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is *** problem is an important component of many machine learning techniques with data parallelism,such as deep learning and federated *** propose a distributed primal-dual stochastic gradient descent(SGD)algorithm,suitable for arbitrarily connected communication networks and any smooth(possibly nonconvex)cost *** show that the proposed algorithm achieves the linear speedup convergence rate O(1/(√nT))for general nonconvex cost functions and the linear speedup convergence rate O(1/(nT)) when the global cost function satisfies the Polyak-Lojasiewicz(P-L)condition,where T is the total number of *** also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global *** demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms.

关键词： Distributed nonconvex optimization linear speedup Polyak-Lojasiewicz(P-L)condition primal-dual algorithm stochastic gradient descent

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A Conflict-Reducing Path Planning Algorithm in Automated Warehouses

A Conflict-Reducing Path Planning Algorithm in Automated War...

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IEEE International Conference on Networking, Sensing and control

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

ISBN: (纸本)9781665440493

With the development of modern logistics industry, automated warehouses are becoming more and more widely used. An automated guided vehicle (AGV) is often used to carry goods in warehouse. Under specific limitations of the road layout, AGVs are prone to conflict when moving. According to the layout characteristics of automated warehouses, this paper proposes a conflict-reducing path planning algorithm, which is an improvement of A-star algorithm. The conflict cost and turn cost are introduced to the algorithm to reduce the conflict probability and the number of turns of paths. Through simulation comparison, it is verified that the algorithm can reduce the probability of conflicts among AGVs and improve the overall efficiency of multi-AGV systems.

关键词： Industries Costs Remotely guided vehicles Roads Layout Path planning Sensors

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A novel hierarchical charging algorithm for the AGV dispatching problem in a multi-robot system

A novel hierarchical charging algorithm for the AGV dispatch...

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IEEE International Conference on Networking, Sensing and control

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

ISBN: (纸本)9781665440493

Charging problem for the AGVs (automated guided vehicles) in a multi-robot system based on a real-world intelligent warehouse aims to maximize the transportation efficiency of AGVs considering the charging process. For this purpose, a hierarchical charging algorithm is presented by taking into account both the continuity of transportation and the charging efficiency. A multi-level threshold scheme is designed to reduce the impact of the charging process on AGV scheduling. The numerical experiment results indicate that at the same charging rate, the number of completed tasks by AGVs can be increased from 18 to 28 an hour compared with traditional charging algorithm thus the efficiency can be improved from 34.62% to 51.86% correspondingly, which shows the superior performance of the presented algorithm.

关键词： Remotely guided vehicles Job shop scheduling Service robots Transportation Robot sensing systems Real-time systems Dispatching

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Improved radar localization on lidar maps using shared embedding

arXiv

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arXiv 2021年

作者： Yin, Huan Wang, Yue Xiong, Rong The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang China

We present a heterogeneous localization framework for solving radar global localization and pose tracking on pre-built lidar maps. To bridge the gap of sensing modalities, deep neural networks are constructed to create shared embedding space for radar scans and lidar maps. Herein learned feature embeddings are supportive for similarity measurement, thus improving map retrieval and data matching respectively. In RobotCar and MulRan datasets, we demonstrate the effectiveness of the proposed framework with the comparison to Scan Context and RaLL. In addition, the proposed pose tracking pipeline is with less neural networks compared to the original RaLL. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical radar

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A Dynamic Joint Real-time Scheduling Strategy of Truck and Yard Crane in Container Terminals

A Dynamic Joint Real-time Scheduling Strategy of Truck and Y...

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IEEE International Conference on Networking, Sensing and control

作者： Xiaojie Jin Xingkai Wang Weimin Wu Zhenrui Rong Quanling Zhang State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (纸本)9781665440493

With the continuous growth of port container throughput, it is difficult to meet the port production demand by simply configuring automation equipments to improve the operation efficiency of machinery. The container truck scheduling and yard crane scheduling are the two important scheduling links in container terminals. At the same time, there is a tight coupling between them. Thus, the joint scheduling of container trucks and yard cranes is necessary to improve the operation efficiency of container terminals. In this paper, the joint real-time scheduling of trucks and yard cranes is mathematically modeled, and is solved by the elite genetic algorithm. Finally, a variety of scheduling strategies are compared to verify the effectiveness of the proposed strategy.

关键词： Cranes Loading Production Containers Dynamic scheduling Throughput Real-time systems

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Efficient learning of goal-oriented push-grasping synergy in clutter

arXiv

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arXiv 2021年

作者： Xu, Kechun Yu, Hongxiang Lai, Qianen Wang, Yue Xiong, Rong State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

—We focus on the task of goal-oriented grasping, in which a robot is supposed to grasp a pre-assigned goal object in clutter and needs some pre-grasp actions such as pushes to enable stable grasps. However, in this task, the robot gets positive rewards from environment only when successfully grasping the goal object. Besides, joint pushing and grasping elongates the action sequence, compounding the problem of reward delay. Thus, sample inefficiency remains a main challenge in this task. In this paper, a goal-conditioned hierarchical reinforcement learning formulation with high sample efficiency is proposed to learn a push-grasping policy for grasping a specific object in clutter. In our work, sample efficiency is improved by two means. First, we use a goal-conditioned mechanism by goal relabeling to enrich the replay buffer. Second, the pushing and grasping policies are respectively regarded as a generator and a discriminator and the pushing policy is trained with supervision of the grasping discriminator, thus densifying pushing rewards. To deal with the problem of distribution mismatch caused by different training settings of two policies, an alternating training stage is added to learn pushing and grasping in turn. A series of experiments carried out in simulation and real world indicate that our method can quickly learn effective pushing and grasping policies and outperforms existing methods in task completion rate and goal grasp success rate by less times of motion. Furthermore, we validate that our system can also adapt to goal-agnostic conditions with better performance. Note that our system can be transferred to the real world without any fine-tuning. Our code is available at https://***/xukechun/Efficient_goaloriented_push-grasping_synergy Copyright © 2021, The Authors. All rights reserved.

关键词： Deep learning

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

arXiv

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arXiv 2021年

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

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. Copyright © 2021, The Authors. All rights reserved.

关键词： Image segmentation

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A Decision-support Framework for Port Container Stowage Plan

A Decision-support Framework for Port Container Stowage Plan

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IEEE International Conference on Networking, Sensing and control

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

ISBN: (纸本)9781665440493

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.

关键词： International trade Loading Transportation Containers Stability analysis Sensors Safety

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