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Realizing high-speed target tracking by using multi-rate feedforward predictive control for the acquisition, tracking, and pointing system

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Defence Technology 2025年

作者： Li, Hang Peng, Gaoliang Shan, Xiaobiao Zhao, Mingyuan Zhang, Wei Wang, Jinghan Cheng, Feng State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China College of Information Science and Technology Eastern Institute of Technology Ningbo315200 China

The acquisition, tracking, and pointing (ATP) system is widely used in target tracking, counter-UAV operations, and other related fields. As UAV technology develops, there is a growing demand to enhance the tracking capabilities of ATP systems. However, in practical applications, ATP systems face various design constraints and functional limitations, making it infeasible to indefinitely improve hardware performance to meet tracking requirements. As a result, tracking algorithms are required to execute increasingly complex tasks. This study introduces a multi-rate feedforward predictive controller to address issues such as low image feedback frequency and significant delays in ATP systems, which lead to tracking jitter, poor tracking performance, low precision, and target loss. At the same time, the proposed approach aims to improve the tracking capabilities of ATP systems for high-speed and highly maneuverable targets under conditions of low sampling feedback rates and high feedback delays. The method suggested is also characterized by its low order, fast response, and robustness to model parameter variations. In this study, an actual ATP system is built for target tracking test, and the proposed algorithm is fully validated in terms of simulation and actual system application verification. Results from both simulations and experiments demonstrate that the method effectively compensates for delays and low sampling rates. For targets with relative angular velocities ranging from 0 to 90°/s and angular accelerations between 0 and 470°/s2, the system improved tracking accuracy by 70.0%–89.9% at a sampling frequency of 50 Hz and a delay of 30 m s. Moreover, the compensation algorithm demonstrated consistent performance across actuators with varying characteristics, further confirming its robustness to model insensitivity. In summary, the proposed algorithm considerably enhances the tracking accuracy and capability of ATP systems for high-speed and highly maneuverable ta

关键词： Predictive control systems

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STVO: Spatial-Temporal Constrained Velocity Obstacle for Safe Navigation among Pedestrians

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IEEE Transactions on Vehicular Technology 2025年

作者： Song, Yichen Wang, Runhua Bi, Qingchen Pan, Zhangchao Gao, Haiming Zhang, Xuebo Nankai University College of Artificial Intelligence Institute of Robotics and Automatic Information System The Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China

This paper presents a novel motion planning method that safely navigates the unmanned ground vehicle (UGV) among pedestrian-rich environments by constructing the spatial-temporal constrained velocity obstacle (STVO) region. Compared with existing velocity obstacle (VO) type-based methods, the novelty of this work is twofold: 1) An innovative temporal constraint is introduced into the velocity space, also playing the role as an adaptive collision time constraint to dynamically adjust the velocity obstacle region according to real-time perceived pedestrian density;2) The spatial constraint is proposed to foresee and evade potential entrapments for the UGV, by carefully considering the position relationship between the UGV and the VO region. Additionally, a velocity resampling mechanism is further designed to prevent the UGV from being trapped. Above techniques augments the navigation flexibility and safety of the UGV, thereby significantly improves the success rate of practical navigation in dynamic and challenging pedestrian environments. Extensive simulations and real-world experiments have been conducted, especially the experiment in pedestrian-rich school cafeteria demonstrating satisfactory practicality of our approach. (Supplementary video link: https://***/xt4KosuPMYs). © 1967-2012 IEEE.

关键词： Pedestrian safety

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Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 27-33页

作者： ZHAO Yanfei XIAO Peng WANG Jingchuan GUO Rui Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai200240China State Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240China State Grid Intelligence Technology Co. Ltd.Jinan250013China

Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior *** order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic *** last,comparative experiments were carried out in the real *** show that our method is superior in terms of safety,comfort and docking accuracy.

关键词： semi-autonomous navigation mobile robot semantic map voice interaction

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Augmented Reality Based Navigation system for Endoscopic Transnasal Optic Canal Decompression

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 34-42页

作者： FU Hang XU Jiangchang LI Yinwei ZHOU Huifang CHEN Xiaojun Institute of Biomedical Manufacturing and Life Quality Engineering State Key Laboratory System and VibrationSchool of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Department of Ophthalmology Shanghai Ninth People's HospitalShanghai Jiao Tong University School of MedicineShanghai 200011China Institute of Medical Robotics Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology Shanghai 200011China

Endoscopic transnasal optic nerve decompression surgery plays a crucial role in minimal invasive treatment of complex traumatic optic ***,a major challenge faced during the procedure is the inability to visualize the optic nerve *** address this issue,an endoscopic image-based augmented reality surgical navigation system is developed in this *** system aims to virtually fuse the optic nerve onto the endoscopic images,assisting surgeons in determining the optic nerve’s position and reducing surgical ***,a calibration algorithm based on a checkerboard grid of immobile points is proposed,building upon existing calibration ***,to tackle accuracy issues associated with augmented reality technology,an optical navigation and visual fusion compensation algorithm is proposed to improve the intraoperative tracking *** evaluate the system’s performance,model experiments were meticulously designed and *** results confirm the accuracy and stability of the proposed system,with an average tracking error of(0.99±0.46)*** outcome demonstrates the effectiveness of the proposed algorithm in improving the augmented reality surgical navigation system’s ***,the system successfully displays hidden optic nerves and other deep tissues,thus showcasing the promising potential for future applications in orbital and maxillofacial surgery.

关键词： optic nerve decompression endoscopy augmented reality surgical navigation

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Centra-Net: A Centralized Network for Visual Localization Spanning Multiple Scenes

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IEEE Transactions on Multimedia 2025年

作者： Jiang, Zhiqiang Dai, Kun Wang, Ke Xie, Tao Fan, Zhendong Li, Ruifeng Kang, Peng Zhao, Lijun Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150006 China Harbin Institute of Technology Zhengzhou Research Institute Zhengzhou450000 China Jianghuai Advance Technology Center Hefei230000 China

We present Centra-Net, a centralized network that concurrently optimizes visual localization over numerous scenes under heterogeneous dataset domains. Centra-Net exemplifies storage efficiency by amalgamating multiple models with task-shared parameters into a singular cohesive structure. Technically, we develop a basic feature extraction unit (BFEU) with two parallel branches: one dedicated to local feature extraction and the other adept at adaptively generating a task-specific attention mask for feature calibration, thus bolstering its feature extraction capability across diverse scenes. Based on the BFEU, we introduce a filter-wise sharing mechanism (FSM) that adaptively determines parameter sharing within the unit, thus facilitating fine-grained parameter allocation. The key insight of FSM resides in reconceptualizing the parameter sharing of the unit as a learnable paradigm, enabling the determination of shared parameters to be made post-training. Finally, we suggest a complexity-prioritized gradient algorithm (CPGA) that capitalizes on task complexity to attain a harmonious learning space for various tasks, thus safeguarding optimal performances across all tasks. Through rigorous experiments on numerous benchmarks, Centra-Net demonstrates a notable edge over existing state-of-the-art works while operating with a significantly reduced parameter footprint. © 1999-2012 IEEE.

关键词： Deep learning Feature extraction Task complexity Visual localization

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Study on wear mechanism of small ball-end grinding wheel and surface integrity of complex component under high-speed machining condition

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Wear 2025年

作者： Qin, Biao Liu, Henan Cheng, Jian Tian, Jinchuan Sun, Jiangang Chen, Mingjun School of Mechatronics Engineering Harbin Institute of Technology Heilongjiang Harbin150001 China State Key Laboratory of Robotics and System Harbin Institute of Technology Heilongjiang Harbin150001 China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou450000 China

The small ball-end fine diamond grinding wheel is well-suited for machining complex components with small curved surface structures, demonstrating high-precision and high-quality machining capabilities. By increasing the speed of the workpiece, the issue of poor grinding performance caused by the small diameter of the ball-end grinding wheel can be effectively overcome. However, this strategy inevitably increases wheel wear and affects surface integrity. To address these challenges, this paper systematically investigates the grinding characteristics of the small ball-end grinding wheel. First, grinding experiments were performed to investigate the influence of workpiece speed, feed rate, and grinding depth on the material removal rate, wheel wear, and surface integrity. Then, the wear mechanism of the grinding wheel was analyzed. The wear modes of the grinding wheel at high workpiece speeds include metal adhesive wear and abrasive grain fracture, which enhance the self-sharpening of the grinding wheel while accelerating its wear. Furthermore, the surface morphology creation mechanism of fused silica under different material removal modes was revealed. Moreover, the correlation between material removal rate and surface roughness caused by wheel wear was revealed. A high-speed grinding strategy was subsequently proposed based on the relationship between the grinding characteristics and grinding parameters of the small ball-end grinding wheel under various grinding conditions. Finally, the feasibility of this grinding strategy was validated through its application to the machining of the complex curved fused silica hemispherical resonator (HSR). Experimental results indicate that under the high workpiece speed condition, the best surface roughness of HSR decreases from 90.5 nm to 62.2 nm, while the maximum grinding wheel wear increases from 9.7 μm to 11.5 μm, with minimal impact on surface integrity. Therefore, the high-speed grinding strategy proposed in this study ho

关键词： Fused silica

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Synthesized colonoscopy dataset from high-fidelity virtual colon with abnormal simulation

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Computers in Biology and Medicine 2025年 186卷 109672-109672页

作者： He, Dongdong Liu, Ziteng Yin, Xunhai Liu, Hao Gao, Wenpeng Fu, Yili School of Life Science and Technology Harbin Institute of Technology Harbin150080 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150080 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Department of Gastroenterology The First Affiliated Hospital of Harbin Medical University Harbin150001 China

With the advent of the deep learning-based colonoscopy system, the need for a vast amount of high-quality colonoscopy image datasets for training is crucial. However, the generalization ability of deep learning models is challenged by the limited availability of colonoscopy images due to regulatory restrictions and privacy concerns. In this paper, we propose a method for rendering high-fidelity 3D colon models and synthesizing diversified colonoscopy images with abnormalities such as polyps, bleeding, and ulcers, which can be used to train deep learning models. The geometric model of the colon is derived from CT images. We employed dedicated surface mesh deformation to mimic the shapes of polyps and ulcers and applied texture mapping techniques to generate realistic, lifelike appearances. The generated polyp models were then attached to the inner surface of the colon model, while the ulcers were created directly on the inner surface of the colon model. To realistically model blood behavior, we developed a simulation of the blood diffusion process on the colon's inner surface and colored vertices in the traversed region to reflect blood flow. Ultimately, we generated a comprehensive dataset comprising high-fidelity rendered colonoscopy images with the abnormalities. To validate the effectiveness of the synthesized colonoscopy dataset, we trained state-of-the-art deep learning models on it and other publicly available datasets and assessed the performance of these models in abnormal classification, detection, and segmentation. Notably, the models trained on the synthesized dataset exhibit an enhanced performance in the aforementioned tasks, as evident from the results. © 2025 Elsevier Ltd

关键词： Digital elevation model

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Optimization-free Smooth Control Barrier Function for Polygonal Collision Avoidance

arXiv

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arXiv 2025年

作者： Wu, Shizhen Fang, Yongchun Sun, Ning Lu, Biao Liang, Xiao Zhao, Yiming Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin300353 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China

Polygonal collision avoidance (PCA) is short for the problem of collision avoidance between two polygons (i.e., polytopes in planar) that own their dynamic equations. This problem suffers the inherent difficulty in dealing with non-smooth boundaries and recently optimization-defined metrics, such as signed distance field (SDF) and its variants, have been proposed as control barrier functions (CBFs) to tackle PCA problems. In contrast, we propose an optimization-free smooth CBF method in this paper, which is computationally efficient and proved to be nonconservative. It is achieved by three main steps: a lower bound of SDF is expressed as a nested Boolean logic composition first, then its smooth approximation is established by applying the latest log-sum-exp method, after which a specified CBF-based safety filter is proposed to address this class of problems. To illustrate its wide applications, the optimization-free smooth CBF method is extended to solve distributed collision avoidance of two underactuated nonholonomic vehicles and drive an underactuated container crane to avoid a moving obstacle respectively, for which numerical simulations are also performed. © 2025, CC BY.

关键词： Magnetic levitation vehicles

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Diverse Gaussian Sampling for Human Motion Prediction 16th

Diverse Gaussian Sampling for Human Motion Prediction

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16th International Conference on Social robotics, ICSR + InnoBiz 2024

作者： Luo, Jiefu Wang, Jiansheng Liu, Zhenfei Cheng, Jun Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Beijing China The Chinese University of Hong Kong Hong Kong Department of Pediatric Orthopedics Shenzhen Children’s Hospital Guangdong Shenzhen518000 China

ISBN: (纸本)9789819611508

In many industrial applications, it is necessary to obtain accurate human motion prediction. The prediction of human movement based on a 3D skeleton, which forecasts future postures using the human skeletal structure, significantly aids in enabling machines to understand human behavior and react more intelligently. Additionally, by predicting human actions, potential dangers can be perceived, especially in safety-related issues, necessitating a broader range of predictions. In this paper, considering the greater diversity generated by Variational Autoencoders (VAEs), we employ VAEs for prediction. In contrast to other studies, our primary focus is on obtaining more diverse samples. Extensive experiments demonstrate that our proposed model performs well on the Human 3.6M [35] and HumanEva-I [36] datasets. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Prediction models

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Robust Safety Critical Control Under Multiple State and Input Constraints: Volume Control Barrier Function Method

arXiv

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arXiv 2025年

作者： Dong, Jinyang Wu, Shizhen Liu, Rui Liang, Xiao Lu, Biao Fang, Yongchun Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin300071 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China

In this paper, the safety-critical control problem for uncertain systems under multiple control barrier function (CBF) constraints and input constraints is investigated. A novel framework is proposed to generate a safety filter that minimizes changes to reference inputs when safety risks arise, ensuring a balance between safety and performance. A nonlinear disturbance observer (DOB) based on the robust integral of the sign of the error (RISE) is used to estimate system uncertainties, ensuring that the estimation error converges to zero exponentially. This error bound is integrated into the safety-critical controller to reduce conservativeness while ensuring safety. To further address the challenges arising from multiple CBF and input constraints, a novel Volume CBF (VCBF) is proposed by analyzing the feasible space of the quadratic programming (QP) problem. To ensure that the feasible space does not vanish under disturbances, a DOB-VCBF-based method is introduced, ensuring system safety while maintaining the feasibility of the resulting QP. Subsequently, several groups of simulation and experimental results are provided to validate the effectiveness of the proposed controller. © 2025, CC BY.

关键词： Quadratic programming

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