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Digital twin and its application in transportation infrastructure 1

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Digital twin and its application in transportation infrastru...

1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Gao, Yan Qian, Shuyue Li, Zihan Wang, Ping Wang, Feiyue He, Qing Southwest Jiaotong University Key Laboratory of High-Speed Railway Engineering Ministry of Education Chengdu China School of Civil Engineering Southwest Jiaotong University Chengdu China Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Beijing China Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665433372

A prevailing challenge lies in how to properly design, construct and maintain transportation infrastructure engineering. Due to the development of sensor technology and computing technology, the amount of equipment monitoring data has multiplied and it causes difficulties in real-time state assessment and prediction under the traditional modeling condition. The introduction of Digital Twin technology, which aims to reflect the performance of the real-world product by simulating a virtual space, can solve these problems effectively. This paper reviews recent applications of four types of transportation infrastructure: railways, highways, bridges, and tunnels. Also, the existing research gaps are identified. © 2021 IEEE.

关键词： Bridges

Three-dimensional target tracking control for a biomimetic underwater vehicle 30

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Three-dimensional target tracking control for a biomimetic u...

30th International Ocean and Polar Engineering Conference, ISOPE 2020

作者： Bai, Ge Wang, Rui Wang, Yu Wang, Shuo State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781880653845

This paper presents a target tracking control method for a biomimetic underwater vehicle named RobCutt-II. The RobCutt-II is propelled by double undulatory fins which are distributed on both sides. In order to implement target tracking and observation in a certain distance, we propose a method by decoupling the target tracking control problem into distance, heading and depth control problems. Based on this idea, we design a target tracking controller composed of a navigation system, a distance controller, a heading controller, a depth controller and a switching logic controller. The simulation results verify the effectiveness of the proposed method on the biomimetic underwater vehicle. © 2020 by the International Society of Offshore and Polar Engineers (ISOPE).

关键词： controllers

What will robots be like in the future?

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National Science Review 2019年第5期6卷 1059-1061页

作者： Yanfeng Lu Weijie Zhao the State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences NSR

Robots are changing our lives:sweeping robots patrol our living rooms; interactive robots accompany our children; industrial robots assemble vehicles; rescue robots search and save lives in catastrophes; medical robots perform surgeries in *** better understand robots’challenges and impact, National Science Review (NSR) interviewed Professor Toshio Fukuda, who is one of the world’s most representative robotics experts and has developed a number of bionic robots and micro/nano-robots.

关键词： NSR China What will robots be like in the future

Oscillation Suppression Method based on Power control Optimization of the Wind Farms 3

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Oscillation Suppression Method based on Power Control Optimi...

3rd IEEE International Power Electronics and Application Conference and Exposition, PEAC 2022

作者： Yang, Jiaqi Wang, Shaojun Li, Zhen Tian, Xu Liu, Bin Liu, Xiangdong Beijing Institute of Technology School of Automation Beijing China Co.Ltd Bayannur Power Supply Bureau Inner Mongolia China State Key Laboratory for Intelligent Control and Decision of Complex Systems Beijing China Beijing University of Mining and Technology Beijing Electric Engineering and Automation Beijing China Tsinghua University Department of Electrical Engineering Beijing China

ISBN: (数字)9781665491419

ISBN: (纸本)9781665491419

Oscillation issues in the grid-connected wind farm system can severely deteriorate the power system security and lead to serious damage. Based on the impedance analysis method, many oscillation suppression methods have been proposed for reshaping the impedance characteristics of system to avoid the risk of oscillations. However, modifying converters' controllers to reshape the wind turbines (WTs) impedance and usage of additional damping devices for reshaping the grid impedance both are time-consuming and costly. Therefore, based on the sequence impedance model of the grid-connected wind farm system, this paper proposes a novel oscillation suppression method by optimizing the power control of wind farm. The system stability margin can be improved by modifying the number of online WTs and the output power of each WT to reshape the impedance of wind farm, under the precondition that the output power demand of wind farm is satisfied. Then, the intelligent particle swarm optimization (PSO) algorithm is used to solve the optimization approach to obtain the number of online WTs with optimal stability margin. Finally, the simulation confirms the effectiveness of the proposed oscillation suppression method. © 2022 IEEE.

关键词： System stability

Conservative-Progressive Collaborative Learning for Semi-supervised Semantic Segmentation

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arXiv 2022年

作者： Fan, Siqi Zhu, Fenghua Feng, Zunlei Lv, Yisheng Song, Mingli Wang, Fei-Yue The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Tsinghua University Beijing China The College of Computer Science and Technology Zhejiang University Hangzhou China

Pseudo supervision is regarded as the core idea in semi-supervised learning for semantic segmentation, and there is always a tradeoff between utilizing only the high-quality pseudo labels and leveraging all the pseudo labels. Addressing that, we propose a novel learning approach, called Conservative-Progressive Collaborative Learning (CPCL), among which two predictive networks are trained in parallel, and the pseudo supervision is implemented based on both the agreement and disagreement of the two predictions. One network seeks common ground via intersection supervision and is supervised by the high-quality labels to ensure a more reliable supervision, while the other network reserves differences via union supervision and is supervised by all the pseudo labels to keep exploring with curiosity. Thus, the collaboration of conservative evolution and progressive exploration can be achieved. To reduce the influences of the suspicious pseudo labels, the loss is dynamic re-weighted according to the prediction confidence. Extensive experiments demonstrate that CPCL achieves state-of-the-art performance for semi-supervised semantic segmentation. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantic Segmentation

Path Planning of Mobile Robot Based on an Improved Genetic Algorithm

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Path Planning of Mobile Robot Based on an Improved Genetic A...

Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Zenghua Chen Gang Xiong Sheng Liu Zhen Shen Yue Li State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China School of Automobile Chang'an University Xi'an China

ISBN: (数字)9781665492270

ISBN: (纸本)9781665492287

In order to solve the problem of premature convergence of the basic genetic algorithm when planning the robot running path, the basic genetic algorithm is improved and optimized. Different population initialization methods are used to initialize multiple populations randomly, so as to improve the diversity of populations; Improve the adaptive strategy and elite strategy of crossover and mutation operators to improve the convergence speed of the algorithm; Add the path tortuosity as the planning index in the fitness function to make the planned path smoother, and add constraints to the model to avoid obstacles; Finally, through the transformation of the coding paradigm of the above improved genetic algorithm, it can run on Flink distributed cluster to obtain faster solution speed, so as to meet the efficiency requirements of path planning in large-scale robot cluster system. The optimized algorithm is compared with the basic genetic algorithm. The simulation results show that the improved algorithm is efficient in robot path planning.

关键词： Sociology Clustering algorithms Path planning Planning Trajectory Statistics Collision avoidance

A Hierarchical Deep Reinforcement Learning Framework for 6-DOF UCAV Air-to-Air Combat

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arXiv 2022年

作者： Chai, Jiajun Chen, Wenzhang Zhu, Yuanheng Yao, Zong-Xin Zhao, Dongbin State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China China

Unmanned combat air vehicle (UCAV) combat is a challenging scenario with continuous action space. In this paper, we propose a general hierarchical framework to resolve the within-vision-range (WVR) air-to-air combat problem under 6 dimensions of degree (6-DOF) dynamics. The core idea is to divide the whole decision process into two loops and use reinforcement learning (RL) to solve them separately. The outer loop takes into account the current combat situation and decides the expected macro behavior of the aircraft according to a combat strategy. Then the inner loop tracks the macro behavior with a flight controller by calculating the actual input signals for the aircraft. We design the Markov decision process for both the outer loop strategy and inner loop controller, and train them by proximal policy optimization (PPO) algorithm. For the inner loop controller, we design an effective reward function to accurately track various macro behavior. For the outer loop strategy, we further adopt a fictitious self-play mechanism to improve the combat performance by constantly combating against the historical strategies. Experiment results show that the inner loop controller can achieve better tracking performance than fine-tuned PID controller, and the outer loop strategy can perform complex maneuvers to get higher and higher winning rate, with the generation evolves. Copyright © 2022, The Authors. All rights reserved.

关键词： Reinforcement learning

A Multi-population Integrated Approach for Capacitated Location Routing

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arXiv 2024年

作者： He, Pengfei Hao, Jin-Kao Wu, Qinghua School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China Department of Computer Science LERIA University of Angers 2 Boulevard Lavoisier Angers49045 France School of Management Huazhong University of Science and Technology No. 1037 Luoyu Road Wuhan China

The capacitated location-routing problem involves determining the depots from a set of candidate capacitated depot locations and finding the required routes from the selected depots to serve a set of customers whereas minimizing a cost function that includes the cost of opening the chosen depots, the fixed utilization cost per vehicle used, and the total cost (distance) of the routes. This paper presents a multi-population integrated framework in which a multi-depot edge assembly crossover generates promising offspring solutions from the perspective of both depot location and route edge assembly. The method includes an effective neighborhood-based local search, a feasibility-restoring procedure and a diversification-oriented mutation. Of particular interest is the multi-population scheme which organizes the population into multiple subpopulations based on depot configurations. Extensive experiments on 281 benchmark instances from the literature show that the algorithm performs remarkably well, by improving 101 best-known results (new upper bounds) and matching 84 best-known results. Additional experiments are presented to gain insight into the role of the key elements of the algorithm. © 2024, CC BY-NC-ND.

关键词： Cost functions

Simultaneously Calibration of Multi Hand-Eye Robot System Based on Graph

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arXiv 2023年

作者： Zhou, Zishun Ma, Liping Liu, Xilong Cao, Zhiqiang Yu, Junzhi The Institute of Automation Chinese Academy of Sciences Beijing100190 China The College of Electrical Engineering and Computer Science Australian National University Canberra2601 Australia The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The State Key Laboratory for Turbulence and Complex System Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Peking University Beijing100871 China

Precise calibration is the basis for the vision-guided robot system to achieve high-precision operations. systems with multiple eyes (cameras) and multiple hands (robots) are particularly sensitive to calibration errors, such as micro-assembly systems. Most existing methods focus on the calibration of a single unit of the whole system, such as poses between hand and eye, or between two hands. These methods can be used to determine the relative pose between each unit, but the serialized incremental calibration strategy cannot avoid the problem of error accumulation in a large-scale system. Instead of focusing on a single unit, this paper models the multi-eye and multi-hand system calibration problem as a graph and proposes a method based on the minimum spanning tree and graph optimization. This method can automatically plan the serialized optimal calibration strategy in accordance with the system settings to get coarse calibration results initially. Then, with these initial values, the closed-loop constraints are introduced to carry out global optimization. Simulation experiments demonstrate the performance of the proposed algorithm under different noises and various hand-eye configurations. In addition, experiments on real robot systems are presented to further verify the proposed method. © 2023, CC BY-SA.

关键词： Multipurpose robots