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第33届中国控制与决策会议

作者： Ningcun Xu Xiwei Peng Liang Peng Zeng-Guang Hou Institute of Intelligent Sensing & Motion Control School of AutomationBeijing Institute of Technology The State Key Laboratory for Management and Control of Complex Systems(SKL-MCCS) Institute of AutomationChinese academy of Science

ISBN: (纸本)9781665431293

In order to make up for the shortcomings of a single inertial sensor,which is easily disturbed and unable to directly describe the periodic characteristics of gait,a novel gait events detection algorithm is proposed which is based on the invariant characteristics of hip joint *** healthy volunteers conducted a walking experiment over the ground,who were equipped with motion capture device and insole with *** hip angle derived from motion capture device were applied to detect gait events,heel stride(HS) and toe off(TO).And the gait events detected by ground reactor force(GRF) were taken as the reference *** mean absolute difference of HS is 28±42 ms,and the mean absolute difference of TO is 27 ± 43 ms. And the confidence levels of the two gait events are 97.5% and 99.2%,*** results demonstrate that the proposed gait events detection algorithm is reliability and has potential clinical application value.

关键词： gait event inertial sensor hip joint kinematics statistical analysis

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

Research on Container Slot Planning for Coordinated Operatio...

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IEEE International Conference on Networking, Sensing and control

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

ISBN: (纸本)9781665440493

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.

关键词： Cranes Heuristic algorithms Stacking Containers Pareto optimization Planning Sensors

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Battery Charge Dispatching in Multi-robot systems

Battery Charge Dispatching in Multi-robot Systems

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IEEE International Conference on Networking, Sensing and control

作者： Zichao Xing Weimin Wu Haoyi Niu Ruifen Hu State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (纸本)9781665440493

Multi-robot systems (MRSs) attract more and more attention due to their efficiency and safety. In a practical scenario, robots need to work for a long time without human intervention, which requires the robots do not run out of power. The battery charging strategy of most systems uses a fixed threshold or fixed periods to determine when robots should be charged. It does not consider the system task situation, nor the situation of charging station (CS) competition. This paper proposes an efficient charge dispatching strategy, which can ensure that a robot firstly completes a task quickly when it is scheduled to work and firstly be charged to be ready for a subsequent task when it is idle. For the case that multiple robots compete for the same CS, we designe a bidding strategy to determine which robot should be serviced. A rule-based charging strategy is used to compare with the proposed charge dispatching strategy in this paper. The results show that our method performs better in terms of stability and efficiency.

关键词： Conferences Robot sensing systems control systems Dispatching Batteries Sensors Safety

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Nonlinear industrial process fault diagnosis with latent label consistency and sparse Gaussian feature learning

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Journal of Central South University 2022年第12期29卷 3956-3973页

作者： LI Xian-ling ZHANG Jian-feng ZHAO Chun-hui DING Jin-liang SUN You-xian Science and Technology on Thermal Energy and Power Laboratory Wuhan 2nd Ship Design and Research InstituteWuhan 430205China State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China State Key Laboratory of Synthetical Automation for Process Industries(Northeastern University) Shenyang 110819China

With the increasing complexity of industrial processes, the high-dimensional industrial data exhibit a strong nonlinearity, bringing considerable challenges to the fault diagnosis of industrial processes. To efficiently extract deep meaningful features that are crucial for fault diagnosis, a sparse Gaussian feature extractor(SGFE) is designed to learn a nonlinear mapping that projects the raw data into the feature space with the fault label dimension. The feature space is described by the one-hot encoding of the fault category label as an orthogonal basis. In this way, the deep sparse Gaussian features related to fault categories can be gradually learned from the raw data by SGFE. In the feature space,the sparse Gaussian(SG) loss function is designed to constrain the distribution of features to multiple sparse multivariate Gaussian distributions. The sparse Gaussian features are linearly separable in the feature space, which is conducive to improving the accuracy of the downstream fault classification task. The feasibility and practical utility of the proposed SGFE are verified by the handwritten digits MNIST benchmark and Tennessee-Eastman(TE) benchmark process,respectively.

关键词： nonlinear fault diagnosis multiple multivariate Gaussian distributions sparse Gaussian feature learning Gaussian feature extractor

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Efficient Trajectory Generation Based on Traversable Planes in 3D Complex Architectural Spaces

arXiv

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arXiv 2025年

作者： Zhang, Mengke Tian, Zhihao Xia, Yaoguang Xu, Chao Gao, Fei Cao, Yanjun The State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Huzhou Institute Zhejiang University Huzhou Key Laboratory of Autonomous System Huzhou313000 China China Tobacco Zhejiang Industrial Co. Ltd. Hangzhou310024 China

With the increasing integration of robots into human life, their role in architectural spaces where people spend most of their time has become more prominent. While motion capabilities and accurate localization for automated robots have rapidly developed, the challenge remains to generate efficient, smooth, comprehensive, and high-quality trajectories in these areas. In this paper, we propose a novel efficient planner for ground robots to autonomously navigate in large complex multi-layered architectural spaces. Considering that traversable regions typically include ground, slopes, and stairs, which are planar or nearly planar structures, we simplify the problem to navigation within and between complex intersecting planes. We first extract traversable planes from 3D point clouds through segmenting, merging, classifying, and connecting to build a plane-graph, which is lightweight but fully represents the traversable regions. We then build a trajectory optimization based on motion state trajectory and fully consider special constraints when crossing multi-layer planes to maximize the robot’s maneuverability. We conduct experiments in simulated environments and test on a CubeTrack robot in real-world scenarios, validating the method’s effectiveness and practicality. Copyright © 2025, The Authors. All rights reserved.

关键词： Flight paths

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Research on Coupled Task Allocation and Scheduling of Multi-type Robots

Research on Coupled Task Allocation and Scheduling of Multi-...

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IEEE International Conference on Networking, Sensing and control

作者： Xingkai Wang Zichao Xing Weimin Wu Xinyu Chen State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (纸本)9781665440493

Task allocation problem and scheduling problem have always been hot topics in the robotics research field. Both of them can be divided into many categories. Among all these categories, coupled task allocation and scheduling problem (CTASP) is a quite difficult problem, especially for of multi-type robots. However, few researches are conducted on this area. Usually, the CTASP is studied for multi-type robots with fixed execution sequence in the reported literature. However, this paper will study the CTASP for multi-type robots with flexible execution sequence. A two-dimension genetic algorithm (TDGA) is designed to solve this type of problem, combined with rank minimal heuristic (RMH) algorithm to provide an elite strategy. The simulation experiment proves that TDGA can solve this kind of problems efficiently, and the efficiency of hybrid genetic algorithm has been further improved.

关键词： Heuristic algorithms Conferences Robot sensing systems Scheduling Sensors Resource management Task analysis

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

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

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IEEE International Conference on Networking, Sensing and control

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

ISBN: (纸本)9781665440493

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.

关键词： Solid modeling Remotely guided vehicles Heuristic algorithms Production Routing Real-time systems Sensors

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A Hybrid Algorithm to Solve Periodic Vehicle Dispatching Problem with Heterogeneous Vehicles in Logistics Transportation

A Hybrid Algorithm to Solve Periodic Vehicle Dispatching Pro...

引用

IEEE International Conference on Networking, Sensing and control

作者： Xingkai Wang Zichao Xing Weimin Wu Xinyu Chen State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (纸本)9781665440493

The vehicle dispatching problem (VDP) is researching how to arrange vehicles’ transportation, which has been addressed by many scholars. In the field of logistics transportation, the vehicle dispatching problem is presented in a special form, that is, the periodic vehicle dispatching problem (PVDP) with heterogeneous vehicles. In order to solve this problem and improve the efficiency of vehicles, a round recombination algorithm (RRA) with two operators are designed in this paper. And a hybrid algorithm consisting of RRA and simulated annealing algorithm is also proposed to improve RRA. Three groups of experiments are carried out to test the performance of designed algorithms in different scenarios. The results of these experiments prove the effectiveness of RRA. The results also show the superiority of hybrid algorithm to RRA.

关键词： Annealing Conferences Transportation Simulated annealing Production Dispatching Mathematical models

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A Collision Avoidance Algorithm for Idle Robots in Multi-robot System

A Collision Avoidance Algorithm for Idle Robots in Multi-rob...

引用

IEEE International Conference on Networking, Sensing and control

作者： Zichao Xing Weimin Wu Xingkai Wang Ruifen Hu State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

ISBN: (纸本)9781665440493

Multi-robot systems (MRSs) play vital roles in manufacturing systems and logistics systems. In order to improve the efficiency of MRSs, we propose an idle robot collision avoidance algorithm(IRCAA) for idle robots to give way for working robots. In the proposed method, idle robots stop in place for new tasks without returning to robot stations. Once an idle robot gets in the way of working robots, IRCAA will find an avoidance point (AP) for the idle robot to give way. Additionally, no new block or deadlock occurs when the idle robot arrives at the AP. The proposed method in this paper is effective and able to improve the efficiency of MRSs, which is verified by both simulation experiments and actual industrial projects.

关键词： Service robots System recovery Robot sensing systems Sensors Multi-robot systems Collision avoidance Task analysis

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Multi-Stage Decision-Making Skill Learning for Soccer Robot

Multi-Stage Decision-Making Skill Learning for Soccer Robot

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

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

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.

关键词： Training Conferences Computational modeling Decision making Reinforcement learning Real-time systems Generators

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