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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Nada E. Abbas Tamara Petrovic Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Zagreb Croatia

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

This paper presents a decentralized graph-based exploration and inspection framework for Multi-Robot Systems, designed to address challenges in subterranean and largescale environments. Unlike prior works that focus solely on exploration or inspection, this framework integrates volumetric exploration, semantic inspection, and dynamic task allocation into a unified decentralized system. A key novelty of this work is the seamless integration of these modules in a multi-robot setting, allowing UAVs to autonomously coordinate their tasks without relying on centralized control. The framework employs a hierarchical graph structure, utilizing a dense local graph for immediate navigation and a sparse global graph for long-term planning and repositioning. Extensive simulations in large-scale complex-shaped environments demonstrate that the proposed approach improves the completeness of the generated maps, reduces inconsistencies in the constructed mesh, and accelerates the overall exploration-inspection process compared to existing decentralized strategies.

关键词： Semantics Inspection Prediction algorithms Dynamic scheduling Aircraft navigation Robustness Planning Multi-robot systems Resource management Centralized control

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Power Line Following Based on Measurements of the Magnetic Field

Power Line Following Based on Measurements of the Magnetic F...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Goran Vasiljević Dean Martinović Stjepan Bogdan Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Unska 3 University of Zagreb Zagreb Croatia

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

In this paper, we present a method to control the UAV to follow the power line with a specific position and orientation based only on the measurement of the magnetic field generated by the current flow in the power line. In this way, it is possible to localize the UAV with respect to the power line without the need for additional sensors, even in poor visibility conditions. The measurements from four magnetometers attached to the UAV are used to solve an optimization problem that involves determining the relative pose of the UAV with respect to the power line. Based on the relative pose, the UAV is controlled to follow the power line in a predefined position and orientation. Experiments in a test setup have confirmed that the method is applicable in a realistic environment.

关键词： Location awareness Visualization Power measurement Magnetic field measurement Magnetometers Current measurement Position measurement Autonomous aerial vehicles Magnetic fields Optimization

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Relative Localizability and Localization for Multirobot Systems

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IEEE Transactions on robotics 2025年 41卷 2931-2949页

作者： Chen, Liangming Liang, Chenyang Yuan, Shenghai Cao, Muqing Xie, Lihua Southern University of Science and Technology School of System Design and Intelligent Manufacturing Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Shenzhen518055 China Harbin Institute of Technology School of Mechanical Engineering and Automation Shenzhen518055 China Southern University of Science and Technology School of System Design and Intelligent Manufacturing Shenzhen518055 China Nanyang Technological University School of Electrical and Electronic Engineering 639798 Singapore Carnegie Mellon University Robotics Institute PittsburghPA15213 United States

Inter-robot relative positions are crucial for executing various multirobot missions, such as formation maneuvering and collaborative inspection. However, the current sensing technology usually provides part of relative position information, such as inter-robot distances, bearings and angles. This prompts the study of determining inter-robot relative positions, i.e., relative localization, from these partial measurements. Based on the existing results of static networks' localizability and mobile robots' relative localization, we propose a novel concept, relative localizability to describe whether a multirobot system is relatively localizable. Given each robot's self-displacement measurements and inter-robot partial measurements in d (d ≤ 4) sampling instants, we show that a multirobot system's relative localization can be achieved in a purely algebraic and distributed manner, in which the multirobot system is said to be d-step relatively localizable. To make the results more general, we consider that the multirobot system consists of landmarks, leaders, and followers, and that the inter-robot measurements can be distances, bearings or angles. When robots' coordinate frames have different orientations, we show that the given local measurements can be used to determine robots' relative positions and their coordinate frames' relative orientations simultaneously. Simulations and experiments of relative localization for ground robots are conducted to validate the obtained results. © 2004-2012 IEEE.

关键词： Multipurpose robots

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Electric Vehicle Routing Problem with Capacitated Charging Stations and Dynamic Electricity Prices

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IEEE Internet of Things Journal 2025年

作者： He, Zhiye Tian, Yuning Miao, Haoyu Yao, Canqi Yang, Zaiyue Shenzhen Key Laboratory of Control Theory and Intelligent Systems Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities School of System Design and Intelligent Manufacturing Shenzhen518055 China The Hong Kong Polytechnic University Department of Logistics and Maritime Studies Hong Kong Hong Kong

With rapid electrification of transportation systems in recent years, the electric vehicle routing problem (EVRP) has received increasing attention. In order to serve a set of valuable transportation tasks using a fleet of electric vehicles, EVRP intends to jointly determine their routes and the charging schedules, with the aim of optimizing service reward and charging cost under state of charge (SOC) constraints of battery. EVRP is a difficult nonlinear integer program, and due to its intrinsic NP-hardness early EVRP studies often oversimplify the charging process and assume unlimited capacity of charging stations and constant electricity price. The contribution of this paper lies in twofold. First, to better characterize the practical charging process, this paper introduces a new graph model that can take the charging station capacity and dynamic electricity price into full consideration. Second, we design a series of transformation techniques, including reformulation SOC dynamics, Lagrangian relaxation, exact linear programming relaxation, etc, which eventually convert the original EVRP into an approximate linear program. Extensive simulations across 14 instances demonstrate that, the proposed approach is capable of solving large-scale instances over 500 nodes, and is 100 times faster than traditional analytic methods while achieving very close optimality. While comparing with the popular heuristic method ALNS (Adaptive Large Neighborhood Search), our method is several times faster and obtains much better optimality. © 2014 IEEE.

关键词： Charging stations

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Development and Optimization of a WebGL-Based Mechanical Model Simulation Platform 4th

Development and Optimization of a WebGL-Based Mechanical Mod...

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4th International Conference on Mechanical Design and Simulation, MDS 2024

作者： Wang, Xintong Tian, Hao Fang, Jingzhe Zhang, Hualiang Zhang, Tao Software College Shenyang University of Technology Liaoning Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Electrical Engineering Shenyang University of Technology Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9789819778867

The need for mechanical model simulation platforms is growing as a result of the ongoing advancements in digital technology and the mechanical manufacturing sector. The application scope and efficacy of simulation platforms are severely limited by the issue of sluggish rendering performance, which frequently arises when obtaining high-quality rendering. When drawing high demand mechanical models, a lot of processing power is frequently needed, which makes real-time rendering speed unsatisfactory for practical purposes. In order to achieve real-time rendering and simulation of 3D robots, this experiment built and implemented a WebGL-based 3D simulation platform. Additionally, the simulation platform can be optimized by increasing frame rate and rendering speed without sacrificing rendering effect by building a mixed bounding box. © The Author(s) 2025.

关键词： Digital elevation model

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Asymptotic Trajectory Tracking of Stratospheric Airships Based on RISE controllers Under External Uncertainties

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Liu, Can Li, Baoquan Dai, Fengzhi Shi, Wuxi Zhang, Xuebo Tiangong University School of Control Science and Engineering Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems Tianjin300387 China Tianjin University of Science and Technology College of Electronic Information and Automation Tianjin300222 China Nankai University Institute of Robotics and Automatic Information Systems Tianjin Key Laboratory of Intelligent Robotics Tianjin300071 China

For a stratospheric airship under internal and external uncertainties, controller strategies with robust integral sign of the error (RISE) are proposed for asymptotic trajectory tracking control. Specifically, a fully connected neural network (FCNN) is constructed with adaptive weight updating to estimate internal uncertainties of the airship system. Then, a self-tuning RISE controller is designed to track trajectories with compensating external disturbance, which enables gain adjustment in realtime according to system feedback. Based on Lyapunov technique and LaSalle-Yoshizawa corollary extension, system stability is strictly analyzed, and asymptotic convergence performance is obtained for trajectory tracking by the designed controller. Moreover, a RISE controller is designed with fixed gain matrices for the airship based on classic control strategies, and asymptotic tracking is also proved. Finally, numerical simulations are conducted with spiral and hovering control to verify performance of the proposed strategies. © 1965-2011 IEEE.

关键词： Lyapunov methods

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A Gaze-Guided Human Locomotion Intention Recognition and Volitional control Method for Knee-Ankle Prostheses

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IEEE Transactions on Cognitive and Developmental Systems 2025年

作者： Chen, Xinxing Chen, Zhaokai Wang, Yuxuan Yin, Shucong Chen, Chuheng Huang, Jian Fu, Chenglong Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Hubei Key Laboratory of Brain-inspired Intelligent Systems School of Artificial Intelligence and Automation Wuhan430074 China Southern University of Science and Technology Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen518055 China Shanghai Jiaotong University Shanghai China

This paper presents a novel gaze-guided volitional control method for knee-ankle prostheses, designed to enhance the precision and intuitiveness of prosthetic control in complex locomotion tasks. The method utilizes an eye-tracking system coupled with an RGBD camera to estimate 3D gaze points, which are then used to construct a gaze attention map. This map serves as the basis for predicting human locomotion intentions, enabling the prosthesis to accurately step on the intended foot placement. Experimental validation was conducted with both a healthy subject and an amputee subject, focusing on level-ground walking and stair ascent tasks. The results demonstrated that the prosthesis could achieve precise foot placement, with a mean error of 1.22 cm ± 3.14 cm for the healthy subject and 3.40 cm ± 0.66 cm for the amputee subject during level-ground walking. In stair ascent tasks, the system successfully adapted to various gait patterns, with the prosthetic joint angles closely matching natural human movements. The proposed method also effectively reduced the root mean square error (RMSE) of 3D gaze estimation to 2.70 cm, 2.63 cm, and 1.97 cm along the x, y, and z axes, respectively. These findings indicate that the gaze-guided volitional control method not only enhances the functionality of knee-ankle prostheses but also offers a more intuitive interface for users, aligning prosthetic actions with the user’s visual focus and intentions. © 2016 IEEE.

关键词： Knee prostheses

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An Improved Dual Neural Network Method Based on Levy Flight for Multi-Robot Cooperative Area Coverage Search in 3D Unknown Environments

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IEEE Transactions on Cognitive and Developmental Systems 2025年

作者： Zhang, Fangfang Wang, Yongqi Wang, Wenhao Xin, Jianbin Peng, Jinzhu Wang, Yaonan Zhengzhou University School of Electrical and Information Engineering Zhengzhou450001 China State Key Laboratory of Intelligent Agricultural Power Equipment Luoyang471039 China National Engineering Laboratory of Robot Visual Perception and Control Technology School of Robotics Hunan University Changsha410082 China

The research on multi-robot collaborative search in unknown 3D environments, based on bio-inspired neural networks, holds significant value and ***, challenges arise in 3D environments, including excessive turning and vertical movement, as well as the potential for collisions between robots. In response, we propose an improved Glasius Bio-Inspired Neural Network(GBNN) that mitigates decision conflicts among robots and considers the impact of turning and vertical movement on robot decision-making. Furthermore, to address the issue of robots getting trapped in local deadlocks during the search process, we present a dual neural network algorithm based on Levy flights. In the method Dual Glasius Bio-Inspired Neural Network based on Levy Flight(LF-DUAL-GBNN) proposed in this paper, robots obtain random target points through Levy flights and are then guided by a dual neural network to navigate to the vicinity of the target points, thus breaking free from local deadlock states. Finally, we conducted simulation experiments to validate the algorithm's effectiveness. © 2016 IEEE.

关键词： Microrobots

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Robust Finite-Time Containment of Networked Heterogeneous Nonlinear Systems with Intermittent Measurement Only

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IEEE Transactions on Network Science and Engineering 2025年

作者： Tian, Biao Zhang, Hao Cui, Peiyu Wang, Zhuping Yan, Huaicheng Shanghai Key Laboratory of Wearable Robotics and Human-Machine Interaction Tongji University College of Electronic and Information Engineering Department of Control Science and Engineering Shanghai201804 China Ministry of Education Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems China East China University of Science and Technology School of Information Science and Engineering Shanghai200237 China

The robust finite-time containment problem of fully heterogeneous multiagent systems with uncertainties is often challenging, especially when only intermittent output measurement is used. To address the issue posed by the nonidentical system dynamics of multiple leaders, which makes the traditional distributed estimator form for the convex hull inapplicable, a distributed finite-time estimator is constructed for each follower to extract the system matrices and states of leaders. Then, in the output-triggering setting, a finite-time extended state observer driven by intermittent output measurement is developed to reconstruct the uncertainties and unmeasurable states of followers. Meanwhile, the non-continuous output measurement will lead to the differentiation of virtual control laws undefined. To solve this issue, a filtering compensation scheme-based finitetime controller via the backstepping technique is developed for nonlinear followers, ensuring practical finite-time stability (PFTS) of the closed-loop system. It is shown that the proposed algorithm steers each follower into the preset convex combination spanned by the positions of multiple leaders. The capability of the exploited control protocol is verified through simulations and experiments. 2013 IEEE.

关键词： Backstepping

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Sim2Real Learning With Domain Randomization for Autonomous Guidewire Navigation in Robotic-Assisted Endovascular Procedures

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 13842-13854页

作者： Yao, Tianliang Wang, Haoyu Lu, Bo Ge, Jiajia Pei, Zhiqiang Kowarschik, Markus Sun, Lining Seneviratne, Lakmal Qi, Peng Tongji University College of Electronics and Information Engineering Shanghai Institute of Intelligent Science and Technology Department of Control Science and Engineering Shanghai200092 China Shanghai University of Engineering Science School of Electronic and Electrical Engineering Shanghai201620 China Soochow University Robotics and Microsystems Center School of Mechanical and Electrical Engineering Jiangsu Suzhou215131 China Advanced Therapies Siemens Healthineers Ltd. Shanghai201318 China University of Shanghai for Science and Technology Oriental Pan-Vascular Devices Innovation College Shanghai200093 China Bavaria Forchheim91301 Germany Khalifa University KUCARS Department of Mechanical and Nuclear Engineering Abu Dhabi United Arab Emirates Tongji University College of Electronics and Information Engineering Shanghai Institute of Intelligent Science and Technology State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center Shanghai East Hospital Department of Control Science and Engineering School of Medicine Shanghai200092 China

Over the past decade, significant advancements have been made in the research and industrialization of robotic systems for endovascular procedures, yet their clinical application remains relatively limited. Physicians commonly report that these robots lack certain intelligent assistive capabilities during procedures. There has been increasing interest and attempts to apply learning-centered algorithms to the training and enhancement of surgical robot skills. This paper proposes an autonomous navigation algorithm for interventional guidewires that is initially trained solely in a virtual simulation environment and subsequently deployed to a real-world robot. Experimental results demonstrate the feasibility of this approach for real-world applications. The proposed approach can help physicians reduce the learning curve for guidewire manipulation and elevate the robot to a higher level of autonomous operation, thereby breaking through the current bottleneck in the level of intelligence for clinical applications of interventional robots. It also holds promise for bringing intelligent transformation to future interventional procedures. © 2004-2012 IEEE.

关键词： Adversarial machine learning

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