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Research on accurate fire source localization and seconds-level autonomous fire extinguishing technology

Scientific Reports 2025年第1期15卷 1-13页

作者： Ren, Xu Qu, Keyu Guo, Junlong Yin, Hesheng Huang, Bo The State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

With the continuous development of intelligent technology, robots have entered various industries. Firefighting robots have become a hot topic in the field of firefighting and rescue equipment. For firefighting robots, autonomous firefighting technology is the core capability. It includes three steps: flame recognition, fire source location, autonomous firefighting. At present, flame recognition has been widely studied, but the adaptability is poor for different flames. For fire source location technology only rough positioning has been achieved. For autonomous firefighting, the time-consuming water point feedback adjustment method is often used. Those are not suitable for the actual fire rescue. So we proposed to use the visual information, thermal imaging morphological and thermal data of the flame for deep learning, which greatly improves the adaptability of flame recognition. The centimeter-level high-precision positioning of the fire source is achieved. Finally, the proposed water cannon fire source projection method is used to realize rapid water cannon movement instruction generation, and achieve rapid autonomous firefighting. The test results show that the proposed fire source identification algorithm can identify all fire sources up to 15 m at a speed about 15Fps. It can rapid autonomous firefighting within 0.5 s. © The Author(s) 2025.

关键词： Autonomous firefighting High-precision fire positioning Lidar fusion

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Driving mechanism of the morphology evolution involved in the micro-defect healing process of fused silica optics under the non-evaporative CO2 laser irradiation

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Optics and Laser Technology 2025年 188卷

作者： Yang, Zican Xu, Hongguang Zhao, Linjie Cheng, Jian Chen, Mingjun Liu, Zhichao Wang, Shengfei Geng, Feng Xu, Qiao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Department of Mechanical Engineering Pohang University of Science and Technology Pohang37673 Korea Republic of Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou450041 China Research Center of Laser Fusion China Academy of Engineering Physics Chengdu610041 China

Currently, the machining of hard and brittle fused silica material still relies on material removal by contact-based machining tools. Due to the inherent unevenness of grinding wheels and abrasives, surface defects inevitably persist on precision fused silica optics. Recently, the non-contact, non-destructive CO2 laser processing of fused silica begins to attract research attentions. Through the spontaneous micro-flow of the molten materials, the fused silica surface can be smoothed and the defects can be healed without mass loss. However, the micro-flow and material rearrangement in the defect area under laser irradiation involves complex physical interactions such as laser energy deposition, heat transfer, fluid dynamics, and volumetric strain. The contribution mechanisms to the morphological evolution remain unclear, preventing precise control of defects and the achievement of high-quality surfaces. In this work, a new numerical model coupling volume strain with the traditional heat transfer and micro-flow models is established. The computational model shows a high degree of consistency with the experimental results, with a deviation of less than 5%. The contribution of various thermo-mechanical effects, including surface tension, Marangoni force and thermal modification, to the evolution of surface morphology during the defect healing process was revealed. It is found that, the surface tension and thermal strain are the primary factors dominating the surface deformation. Both calculated and experimental results demonstrated that, surface tension is the dominant contributor to the defect healing behavior, with the contribution of the other forces to the defect morphology being less than 1% of that of surface tension. This work can provide guidance for the regulation of the defect healing and other laser processing procedures of fused silica optics. © 2025 Elsevier Ltd

关键词： Irradiation

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Modelling and experimental investigation of micro-dimpled structures milling with spiral trajectory tool reciprocating motion

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Chinese Journal of Aeronautics 2025年第2期 581-600页

作者： Guangzhou WANG Linjie ZHAO Qi LIU Xiguang LI Yazhou SUN Mingjun CHEN School of Mechatronics Engineering Harbin Institute of Technology Centre for Precision Manufacturing DMEMUniversity of Strathclyde State Key Laboratory of Robotics and System Harbin Institute of Technology

To mill fine and well-defined micro-dimpled structures, a machining manner of spiral trajectory tool reciprocating motion, where the tool repeats the process of ‘feed milling±retract±cutting feed±feed milling again' along the spiral trajectory, was proposed. From the kinematics analysis, it is found that the machining quality of micro-dimpled structures is highly dependent on the machining trajectory using spiral trajectory tool reciprocating motion. To reveal this causation, simulation modelling and experimental studies were carried out. A simulation model was developed to quantitatively and qualitatively investigate the influence of the trajectory discretization strategies(constant-angle and constant-arc length) and parameters(discrete angle, discrete arc length, and pitch) on surface texture and residual height of micro-dimpled structures. Subsequently, microdimpled structures were milled under different trajectory discretization strategies and parameters with spiral trajectory tool reciprocating motion. A comprehensive comparison between the milled results and simulation analysis was made based on geometry accuracy, surface morphology and surface roughness of milled dimples. Meanwhile, the errors and factors affecting the above three aspects were analyzed. The results demonstrate both the feasibility of the established simulation model and the machining capability of this machining way in milling high-quality micro-dimpled structures. Spiral trajectory tool reciprocating motion provides a new machining way for milling micro-dimpled structures and micro-dimpled functional surfaces. And an appropriate machining trajectory can be generated based on the optimized trajectory parameters, thus contributing to the improvement of machining quality and efficiency.

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Modeling and design of 3D printed hyperelastic lattice metamaterials with bionic S-shaped stress-strain behaviors

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Materials Horizons 2025年

作者： Dong, Le Zhang, Mengjie Wang, Dong State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Shanghai Key Laboratory of Intelligent Robotics Meta Robotics Institute Shanghai Jiao Tong University Shanghai200240 China

Lattice metamaterials made of stiff polymers, ceramics, and metals have been extensively designed to reproduce the mechanical behaviors of biological tissues, holding promising applications in biomedical devices and tissue engineering. However, lattice metamaterials composed of soft materials have been far less explored due to challenges posed by material nonlinearity and large deformations. Here, hyperelastic lattice metamaterials with curved microstructures are fabricated by 3D printing elastomers and are developed to mimic bionic S-shaped stress-strain behaviors. We propose a design framework for 3D printed hyperelastic lattice metamaterials that integrates digital geometry generation, hierarchical mechanics modeling, and validation by finite element (FE) simulations and experiments. The microstructures are modeled through deriving a Timoshenko-type beam theory governed by hyperelastic strain energy potentials. The model is then combined with the deformation and equilibrium analysis considering non-rigid connections between microstructures to predict the mechanical responses of hyperelastic lattice metamaterials. Using the developed design framework, programmable S-shaped stress-strain behaviors and high fracture strains (over 800%) are achieved. We demonstrate S-shaped stress-strain curves that match skeletal and cardiac muscles and highly stretchable lattice sensors for remote controls. This study provides design methods and theoretical guidelines for hyperelastic lattice metamaterials, holding promise for robotic sensors with bionic performance and functionality. © The Royal Society of Chemistry 2025.

关键词： Stress-strain curves

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Aeroengine remaining useful life prediction via integrating enhanced inverted transformer and spatiotemporal graph learning

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ISA Transactions 2025年

作者： Sun, Shilong Ding, Hao Zhao, Zida Zhou, Yu Wang, Dong Xu, Wenfu School of Robotics and Advanced Manufacturing College of Artificial Intelligence Harbin Institute of Technology Shenzhen China Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai200240 China

Accurate prediction of aeroengine Remaining Useful Life (RUL) is critical for ensuring flight safety, minimizing maintenance costs, and improving operational efficiency. This study proposes a novel model, the Fourier-Enhanced Inverted Transformer with Graph-Augmented Spatiotemporal Modeling (FIT-GSTM), to enhance RUL prediction performance. FIT-GSTM combines an inverted Transformer with a Spatiotemporal Graph Convolutional Network (STGCN) to effectively capture global spatiotemporal dependencies across multi-sensor data. To further enrich feature representation, the model incorporates Fast Fourier Transform (FFT) to extract frequency-domain information and fuses it with time-domain features, enhancing robustness to noise. Additionally, the integration of Memory Tokens and Reversible Instance Normalization (RevIN) strengthens the model's ability to retain long-term dependencies and adapt to heterogeneous data distributions. Experimental evaluations on the C-MAPSS dataset demonstrate that FIT-GSTM achieves superior RUL prediction accuracy and generalization compared to existing methods, highlighting its potential for real-world deployment in aeroengine health management. © 2025 ISA

关键词： Fast Fourier transforms

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Ultrahigh Energy Density and Rapid Response Dielectric Elastomer for Advanced Soft Robots

SSRN

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SSRN 2025年

作者： Du, Chengzhen Yan, Peinan Zou, Jiang Guo, Yutong Pang, Zimo Li, Sijia Chen, Yujie Fan, Qunfu Liu, Hezhou State Key Laboratory of Metal Matrix Composites School of Materials Science and Engineering Shanghai Jiao Tong University Shanghai200240 China Robotics Institute State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China National Engineering Research Center of Special Equipment and Power System for Ship and Marine Engineering Shanghai200030 China

Dielectric elastomer actuators (DEAs) require high energy density to simultaneously achieve high mechanical output while enabling compact and lightweight actuator design. However, the realization of high energy density is constrained by the high driving electric field and the significant hysteretic relaxation. Herein, we present a DE featuring a bimodal-network structure and multiple hydrogen bond interactions, which possesses outstanding properties, including a low Young's modulus, optimal dielectric properties, and low mechanical loss. The DE achieves a maximum actuation strain of 200% at a low driving electric field of 60 V μm-1 with a rapid response. Remarkably, it exhibits an output force of 0.95 N and an ultrahigh specific energy of 283 J kg-1, approximately 7 times that of natural muscle. A series of soft robots with different structures and functions are fabricated to showcase the immense potential of our DE in various applications. This work provides a novel strategy to fabricate high performance artificial muscles for soft robotics. © 2025, The Authors. All rights reserved.

关键词： Elastomers

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Ultrahigh energy density and rapid response dielectric elastomer for advanced soft robots

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Chemical engineering Journal 2025年 515卷

Dielectric elastomer actuators (DEAs) require high energy density to simultaneously achieve high mechanical output while enabling compact and lightweight actuator design. However, the realization of high energy density is constrained by the high driving electric field and the significant hysteretic relaxation. Herein, we present a DE featuring a bimodal-network structure and multiple hydrogen bonds interactions, which possesses outstanding properties, including a low Young's modulus, optimal dielectric properties, and low mechanical loss. The DE achieves a maximum actuation strain of 200 % at a low driving electric field of 60 V μm−1 with a rapid response. Remarkably, it exhibits an output force of 0.95 N and an ultrahigh specific energy of 283 J kg−1, approximately 7 times that of natural muscle. A series of soft robots with different structures and functions are fabricated to showcase the immense potential of our DE in various applications. This work provides a novel strategy to fabricate high performance artificial muscles for soft robotics. © 2025 Elsevier B.V.

关键词： Dielectric properties of solids

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Layered structural engineering of Bi 2 O 3 /PP and WO 3 /PP composites for γ-ray shielding in high energy range: anisotropic attenuation mechanisms via Monte Carlo simulation and experiments

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Journal of Materials Research and Technology 2025年 36卷 10324-10336页

作者： Xiangjie Duan Jie Zhao Shuaida Song Na Zhou Jizhuang Fan Bo Tian Yunchen Du State Key Laboratory of Space Power-Sources School of Chemistry and Chemical Engineering Harbin Institute of Technology Harbin 150001 People's Republic of China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150006 People's Republic of China Heilongjiang Institute of Atomic Energy Heilongjiang Academy of Sciences Harbin 150081 People's Republic of China

The development of non-toxic and flexible polymer-based shielding composites has become a research hotspot due to the severe harm of γ ray to living organisms, mechanical equipment, and environment. However, the γ-ray shielding performance of polymer-based composites in high-energy range remains unsatisfactory. Herein, FLUKA Monte Carlo simulations capable of visualizing γ-photon transport behaviors are investigated in Bi 2 O 3 /PP and WO 3 /PP multi-layer composites with various layered configurations. The simulation results reveal significant anisotropic attenuation effects on shielding characteristics caused by layered configurations and incident path of γ-photons relative to the interface position. Subsequently, single-layer, AB, and sandwich-like ABA composites with a fixed thickness of 2.0 mm are experimentally fabricated via melt-mixing and hot press methods. At 1332 keV, sandwich-like WPPBPPWPP composite (WO 3 /PP outer layers + Bi 2 O 3 /PP core) achieves linear attenuation coefficients and radiation protection efficiency of 0.31 cm −1 and 6 %, respectively, which are 29 % higher than those of single-layer composite. These improvements originate from multiple scattering induced by interlayer interface. Additionally, layered configurations with externally placed high-density fillers (WO 3 ) and internally placed high atomic number fillers (Bi 2 O 3 ) further promote γ-photon attenuation in high-energy range. Experimental results validate the anisotropic shielding trends observed in MC simulations. Moreover, multi-layer composites demonstrate significantly improved energy storage capacity, thermal stability, and oxidation resistance while maintaining comparable to those of single-layer composites. This work provides a scalable strategy for developing non-toxic and flexible shielding materials applicable in nuclear protection, medical devices, and aerospace systems, where lightweight and efficient radiation attenuation are critical.

关键词： Polymer-based composites Multi-layer structural engineering γ-Ray shielding Monte Carlo simulation Anisotropy attenuation Heterogeneous interface

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Model-based contextual reinforcement learning for robotic cooperative manipulation

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engineering Applications of Artificial Intelligence 2025年 155卷

作者： Wang, Wenrui Tang, Qirong Yang, Hao Yang, Chao Ma, Baoping Wang, Shuqing Lin, Rongfu The Laboratory of Robotics and Multibody System School of Mechanical Engineering Tongji University Shanghai201804 China Shanghai Institute of Aircraft Mechanics and Control 100 Zhangwu Road Yangpu District Shanghai200092 China

In large-scale manufacturing and automation, cooperative robotic manipulation requires lower-level controllers to generate specific position or force commands based on real-time information. However, adapting these controllers for different objects or trajectories often demands a complete re-learning process. Contextual Reinforcement Learning (CRL) offers a method to generalize controllers across various contexts, yet it frequently faces instability and inefficiency due to uncertain contact dynamics and external disturbances, especially in real-world industrial environments. To enhance process efficiency and sustainability in robotic systems, a Model-Based Contextual Reinforcement Learning (MCRL) approach is proposed, leveraging metaheuristic solutions to optimize cooperative manipulation. The approach includes a parameterized lower-level control policy, designed using projected inverse dynamics for decoupled control in both constrained and unconstrained subspaces. A probabilistic forward model further enhances the cooperative manipulation process by calculating expected returns and mitigating risk-sensitive biases. Through these optimizations, the MCRL framework efficiently generalizes lower-level policies and improves operational performance. Evaluation on a multi-robot simulation system and a physical dual-arm platform demonstrates the approach's effectiveness in achieving high-quality, sustainable policies for cooperative manipulation tasks, aligning with the goals of improved efficiency and resource utilization in manufacturing. © 2025

关键词： Multipurpose robots

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R-SIEL: a physics-informed learning algorithm for discovering dynamics of serial manipulators

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Expert systems with Applications 2025年 287卷

作者： Omar, Mohamed Li, Ruifeng Wang, Ke Asker, Ahmed State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 China Production and Mechanical Design Engineering Department Faculty of Engineering Mansoura University Mansoura 35516 Egypt Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou 450000 China School of Engineering and Applied Sciences Nile University Giza 12573 Egypt

Dynamic modeling is essential for serial manipulators’ design and control. Multi-body dynamics simulators, such as SIMULINK and Adams, can precisely replicate a robot's dynamic behavior but are incapable of determining its nonlinear dynamic model. This work aims to identify serial manipulators’ dynamics from simulation data, which extends the capability of using an algorithm that combines the Euler-Lagrange method and sparse identification of nonlinear dynamics (SINDy) with physics-based constraints and Akaike Information Criterion (AICc). The algorithm is called Recursive SINDy Euler-Lagrange (R-SIEL). The Euler-Lagrange method is used to construct a preliminary library of symbolic functions. The physics-informed constraints, which utilize the similarities between the symbolic coefficients of the dynamic equations, are employed to decrease the number of functions in the library to get a constrained library. SINDy is equipped with three kinds of constraints: the constrained library, the dataset, and similarities between links’ dynamic equations. The generation of the three distinct datasets—training, constraints, and testing data—uses simulated data from the MATLAB® SIMULINK environment. The algorithms of sequential threshold least-squares and L₀-minimization are coded with the convex optimization package CVX to determine the best dynamic model. The resulting models are tested with the testing dataset, and based on the lowest AICc, the best model is chosen. The proposed algorithm is applied to different serial manipulators: 2DOF robot, Stanford, PRR robot, ABB SCARA, UR5, and KUKA KR4 AGILUS robots. The resulting model is validated with the dynamic model derived using the conventional Euler-Lagrange method. For the considered manipulators, the R-SIEL algorithm shows a high capability to identify the dynamic model compared to the one identified compared to the previous algorithm. © 2025 Elsevier Ltd

关键词： CVX Dynamics of serial manipulators Euler-Lagrange Serial manipulators SIMULINK SINDy

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