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Development and Control of underwater Gliding Robots:A Review

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1543-1560页

作者： Jian Wang Zhengxing Wu Huijie Dong Min Tan Junzhi Yu the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China the State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering ScienceBIC-ESATCollege of EngineeringPeking UniversityBeijing 100871China

As one of the most effective vehicles for ocean development and exploration,underwater gliding robots(uGRs)have the unique characteristics of low energy consumption and strong ***,by borrowing the motion principles of current underwater robots,a variety of novel uGRs have emerged with improving their maneuverability,concealment,and environmental friendliness,which significantly broadens the ocean *** this paper,we provide a comprehensive review of underwater gliding robots,including prototype design and their key *** the perspective of motion characteristics,we categorize the underwater gliding robots in terms of traditional underwater gliders(uGs),hybrid-driven uGs,bio-inspired uGs,thermal uGs,and ***,their buoyancy driven system,dynamic and energy model,and motion control are concluded with detailed ***,we have discussed the current critical issues and future *** review offers valuable insight into the development of next-generation underwater robots well-suited for various oceanic applications,and aims to gain more attention of researchers and engineers to this growing field.

关键词： Buoyancy driven motion control oceanic applications system development underwater gliding robots

Robust global route planning for an autonomous underwater vehicle in a stochastic environment

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Frontiers of Information Technology & Electronic Engineering 2022年第11期23卷 1658-1672页

作者： Jiaxin ZHANG Meiqin LIu Senlin ZHANG Ronghao ZHENG State Key Laboratory of Industrial Control Technology Zhejiang UniversityHangzhou 310027China College of Electrical Engineering Zhejiang UniversityHangzhou 310027China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong UniversityXi'an 710049China

This paper describes a route planner that enables an autonomous underwater vehicle to selectively complete part of the predetermined tasks in the operating ocean area when the local path cost is *** problem is formulated as a variant of the orienteering *** on the genetic algorithm(GA),we propose the greedy strategy based GA(GGA)which includes a novel rebirth operator that maps infeasible individuals into the feasible solution space during evolution to improve the efficiency of the optimization,and use a differential evolution planner for providing the deterministic local path *** uncertainty of the local path cost comes from unpredictable obstacles,measurement error,and trajectory tracking *** improve the robustness of the planner in an uncertain environment,a sampling strategy for path evaluation is designed,and the cost of a certain route is obtained by multiple sampling from the probability density functions of local *** Carlo simulations are used to verify the superiority and effectiveness of the *** promising simulation results show that the proposed GGA outperforms its counterparts by 4.7%–24.6%in terms of total profit,and the sampling-based GGA route planner(S-GGARP)improves the average profit by 5.5%compared to the GGA route planner(GGARP).

关键词： Autonomous underwater vehicle Route planning Genetic algorithm Orienteering problem Stochastic path cost

A modified YOLOv4 detection method for a vision-based underwater garbage cleaning robot

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Frontiers of Information Technology & Electronic Engineering 2022年第8期23卷 1217-1228页

作者： Manjun TIAN Xiali LI Shihan KONG Licheng Wu Junzhi Yu First Research Institute of the Ministry of Public Security of PRC Beijing 100048China School of Information Engineering Minzu University of ChinaBeijing 100081China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

To tackle the problem of aquatic environment pollution,a vision-based autonomous underwater garbage cleaning robot has been developed in our *** propose a garbage detection method based on a modified YOLOv4,allowing high-speed and high-precision object ***,the YOLOv4 algorithm is chosen as a basic neural network framework to perform object *** the purpose of further improvement on the detection accuracy,YOLOv4 is transformed into a four-scale detection *** improve the detection speed,model pruning is applied to the new *** virtue of the improved detection methods,the robot can collect garbage *** detection speed is up to 66.67 frames/s with a mean average precision(mAP)of 95.099%,and experimental results demonstrate that both the detection speed and the accuracy of the improved YOLOv4 are excellent.

关键词： Object detection Aquatic environment Garbage cleaning robot Modified YOLOv4

Trajectory tracking control of a bionic robotic fish based on iterative learning

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Science China(Information Sciences) 2020年第7期63卷 79-87页

作者： Ming WANG Yanlu ZHANG Huifang DONG Junzhi Yu School of Information and Electrical Engineering Shandong Jianzhu University State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering ScienceBIC-ESAT College of Engineering Peking University

A bionic robotic fish has great potential application prospect. High maneuverability swimming control of a bionic robotic fish has been one of the research hotspots in the robotic fish field. In this paper,an iterative learning method has been proposed to solve the trajectory tracking control problem of robotic fish swimming. First, a dynamic model of the multi-joint bionic robotic fish is established. By considering a three-joint robotic fish as an example, the unified expression of the dynamic equation of the three-joint bionic robotic fish is obtained by Lagrange method. Second, the iterative learning controller for controlling the bionic robotic fish is designed. Then the convergence of the iterative learning controller is ***, the trajectory tracking control simulation experiment based on iterative learning is conducted. The simulation results show that the trajectory tracking control method based on iterative learning for a bionic robotic fish is effective.

关键词： bionic robot fish iterative learning trajectory tracking motion control

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群体智能中的追逃围捕问题综述（英文）

Frontiers of Information Technology & Electronic Engineering 2023年第8期 1093-1117页

作者：穆祯鑫潘杰周子烨喻俊志曹璐北京大学工学院先进制造与机器人系湍流与复杂系统国家重点实验室国防科技创新研究院

对于人工系统中涌现出的复杂功能，理解自然界中生物群体行为的内在机制至关重要。本文对生物集群中的一个关键问题—追逃围捕问题进行了全面的综述。首先，从博弈论、控制论与人工智能、生物启发3个不同视角对追逃围捕问题进行了回顾... 详细信息

对于人工系统中涌现出的复杂功能，理解自然界中生物群体行为的内在机制至关重要。本文对生物集群中的一个关键问题—追逃围捕问题进行了全面的综述。首先，从博弈论、控制论与人工智能、生物启发3个不同视角对追逃围捕问题进行了回顾。然后，概述了生物系统和人工系统中追逃围捕问题研究进展，其中捕食者的追捕行为和猎物的逃避行为被概括为捕食者—猎物行为。之后，分别从强追捕者组vs.弱逃避者组、弱追捕者组vs.强逃避者组、相同能力组3个角度分析追逃围捕问题在人工系统中的应用。最后，讨论了未来追逃围捕问题面临的挑战和发展展望。本文为多智能体系统和多机器人系统在不确定动态场景下完成复杂狩猎任务的设计提供了新的见解。

关键词：群体行为追逃问题人工系统生物模型群集运动

基于多个自主水下航行器的分布式协同流场估计

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控制理论与应用 2022年第11期39卷 2036-2046页

作者：何翌郑荣濠张森林刘妹琴浙江大学电气工程学院浙江杭州310027 浙江大学工业控制技术国家重点实验室浙江杭州310027 西安交通大学人工智能与机器人研究所陕西西安710049

本文考虑利用多个自主式水下航行器(AuV)实现流场估计,提出了一种基于树型网络的分布式方法来估计水下流场.在本文中,借助绝对运动积分误差和相对运动积分误差,流场估计问题被描述为求解一个以未知流场为变元的非线性方程组.继而本文在... 详细信息

本文考虑利用多个自主式水下航行器(AuV)实现流场估计,提出了一种基于树型网络的分布式方法来估计水下流场.在本文中,借助绝对运动积分误差和相对运动积分误差,流场估计问题被描述为求解一个以未知流场为变元的非线性方程组.继而本文在多AuV系统内建立一个低通讯成本的树型网络,并在该网络上运行一种分布式算法以求解与流场估计相关的非线性方程组.在该算法中,每个AuV将当前的流场估计值连续地投影到自身拥有的约束方程的解集中,并通过扩散和池化两个步骤在树型网络间传递流场估计值.本文证明了上述算法的收敛性,并通过仿真实验验证了所述分布式协同流场估计方法的有效性.

关键词：流场估计树型结构自主式水下航行器分布式算法非线性Kaczmarz

Line-of-sight based three-dimensional path following control for an underactuated robotic dolphin

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Science China(Information Sciences) 2021年第1期64卷 215-226页

作者： Jincun LIu Zhenna LIu Junzhi Yu State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering ScienceBIC-ESATCollege of EngineeringPeking University Department of Electrical and Automation Shandong Labor Vocational and Technical College State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

This paper investigates the three-dimensional(3-D) path following control problem for an underactuated robotic dolphin. With a comprehensive consideration of the mechanical constraint and swimming principle of the robotic dolphin, a decoupling motion strategy is proposed to produce yaw and pitch maneuvers simultaneously. Then, kinematics and dynamics models for 3-D dolphin-like swimming are established,followed by simulations of the path following control. Furthermore, a novel lookahead based 3-D line-ofsight(LOS) guidance law is developed and implemented to obtain desired attitude angles with its simplicity,intuitiveness, and small computational footprint. Finally, simulation results illustrate the feasibility and effectiveness of the proposed path following control methods.

关键词： robotic dolphin path following 3-D LOS guidance law decoupling motion

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声呐图像自动目标识别技术研究

工业控制计算机 2021年第5期34卷 54-56页

作者：楼冠廷浙江大学电气工程学院浙江杭州310027

提出了一种基于神经网络可视化的声呐图像自动目标识别技术,能够仅依靠样本类别标签实现对声呐图像目标的定位与识别,较大减少了人工成本,也使得方法容易泛化到声呐图像的不同数据集上。该方法首先使用Grad-CAM技术可视化解释神经网络,... 详细信息

提出了一种基于神经网络可视化的声呐图像自动目标识别技术,能够仅依靠样本类别标签实现对声呐图像目标的定位与识别,较大减少了人工成本,也使得方法容易泛化到声呐图像的不同数据集上。该方法首先使用Grad-CAM技术可视化解释神经网络,并作为可视化输入图像目标位置的基本方法,之后与ResNet-18主干模型结合实现了基于神经网络可视化的声呐图像自动目标识别技术的基础模型,并在真实声呐图像数据集上进行了实验验证。针对因为声呐数据集的不丰富而造成的模型目标定位失准的问题,该方法进一步通过迁移预训练参数,优化基础模型提取特征的能力,从而使得该方法在实际定位和识别声呐图像目标时的准确率和鲁棒性有了明显提升。

关键词：自动目标识别神经网络可视化声呐图像