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

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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Comprehensive Performance Optimization of a Novel Anthropomorphic Dexterous Hand

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IEEE robotics and Automation Letters 2025年第7期10卷 6816-6823页

作者： Yifan Ma Weiwei Shang Fei Zhang Shunxiang Pang Shuqing Dai Zhengkun Yi Guotao Li Shuang Cong Department of Automation University of Science and Technology of China Hefei China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China

Grasp and in-hand manipulation of dexterous hands are essential for daily operational tasks. In this study, an optimized design method for a novel anthropomorphic dexterous hand is proposed, which improves the comprehensive performance of grasp and manipulability of the dexterous hand. The constraints of multi-fingered contact force and kinematics are established with full consideration of the applicability to the objects of different sizes and the shape characteristics of finger contact surface. The performance index of in-hand manipulation ability is proposed, and the optimization problem is constructed through the technique for order preference by similarity to ideal solution (TOPSIS) to achieve multi-objective optimization of precision grasp and in-hand manipulation. Finally, simulation and experiment verify the feasibility of our prototype and optimization method. The results show that the in-hand translation space and in-hand rotation range are increased by 20% and 8.5%, respectively. Our dexterous hand has excellent abilities of multi-fingered interaction and in-hand manipulation, which can perform 33 grasp gestures and two/three-fingered in-hand manipulation. This study provides a valuable reference for the design of dexterous hands with anthropomorphic functions.

关键词： Thumb Hands Kinematics Grasping Force Performance analysis IP networks Electronics packaging Cables Accuracy

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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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Design of a SMA actuated freeplay elimination device for stiffness enhancement of a folding fin

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Mechanical systems and Signal Processing 2025年 234卷

作者： Zhang, Rongru Chen, Gang Yue, Honghao Si, Mingyu State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin 150001 China Beijing Institute of Electronic System Engineering Beijing 100854 China

The folding fin, essential for controlling aircraft flight attitude and maintaining stability, is extensively employed in aerospace vehicles. Inevitable freeplay within the structure, due to design, installation, and mechanical wear, reduce the stiffness of the folding fins and impair the aircraft's aerodynamic performance. Therefore, eliminating the freeplay in the folding fin is crucial for enhancing the aircraft's flight accuracy and stability. This paper introduces a novel freeplay elimination device utilizing SMA columns, which neither increases mass nor alters the aircraft's external dimensions. The device effectively alleviates nonlinear issues associated with gaps in the fin system and enhances both the dynamic and static stiffness of the folding fin. A parametric design model for the gap elimination device has been developed, delineating the relationship between the structure and layout of the SMA columns, the actuation temperature, load, and the target gap for elimination. We conducted static load tests along with modal tests at room and elevated temperatures to evaluate the stiffness enhancement performance of the folding fin before and after gap elimination. The experiments verified that the designed gap elimination device significantly enhances both the static and dynamic stiffness of the folding fin. Additionally, the first-order frequency of the folding fin increased by 40 % at room temperature and by 36.7 % at 200 °C. This paper provides quantifiable guidance for the structural and parametric design of gap elimination devices in folding fins. Optimal structural parameters, determined based on aerodynamic loads and gap elimination requirements, enhance the stiffness of the folding fin, thus improving the aircraft's flight performance. © 2025

关键词： Actuator Folding fin Freeplay SMA Stiffness enhancement

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

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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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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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An Iterative Task-Driven Framework for Resilient LiDAR Place Recognition in Adverse Weather

arXiv

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arXiv 2025年

作者： Zhao, Xiongwei Wang, Yang Sun, Qihao Bai, Haojie Xie, Xingxiang Shenzhen518071 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150006 China School of Information Communication Technology Shenzhen Institute of Information Technology Shenzhen518071 China

LiDAR place recognition (LPR) plays a vital role in autonomous navigation. However, existing LPR methods struggle to maintain robustness under adverse weather conditions such as rain, snow, and fog, where weather-induced noise and point cloud degradation impair LiDAR reliability and perception accuracy. To tackle these challenges, we propose an Iterative Task-Driven Framework (ITDNet), which integrates a LiDAR Data Restoration (LDR) module and a LiDAR Place Recognition (LPR) module through an iterative learning strategy. These modules are jointly trained end-to-end, with alternating optimization to enhance performance. The core rationale of ITDNet is to leverage the LDR module to recover the corrupted point clouds while preserving structural consistency with clean data, thereby improving LPR accuracy in adverse weather. Simultaneously, the LPR task provides feature pseudo-labels to guide the LDR module’s training, aligning it more effectively with the LPR task. To achieve this, we first design a task-driven LPR loss and a reconstruction loss to jointly supervise the optimization of the LDR module. Furthermore, for the LDR module, we propose a Dual-Domain Mixer (DDM) block for frequency-spatial feature fusion and a Semantic-Aware Generator (SAG) block for semantic-guided restoration. In addition, for the LPR module, we introduce a Multi-Frequency Transformer (MFT) block and a Wavelet Pyramid NetVLAD (WPN) block to aggregate multi-scale, robust global descriptors. Finally, extensive experiments on the Weather-KITTI, Boreas, and our proposed Weather-Apollo datasets demonstrate that, demonstrate that ITDNet outperforms existing LPR methods, achieving state-of-the-art performance in adverse weather. The datasets and code will be made publicly available at https://***/Grandzxw/ITDNet. © 2025, CC BY.

关键词： Image coding

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Evaluation of motor unit tracking across hand movements by combining high-density surface electromyography with ultrafast ultrasound

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Computers in Biology and Medicine 2025年 193卷 110325-110325页

作者： Yin, Zongtian Chen, Chen Meng, Jianjun Zhu, Xiangyang State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai China Meta Robotics Institute Shanghai Jiao Tong University Shanghai China

Objective: Motor unit (MU) activities provide the primary output from the central nervous system to muscles, and have found wide applications in neurophysiological investigation and human-machine interface. However, the current decoding methods usually struggle with MU tracking across movements. A common compromise is comparing motor unit action potentials extracted from electromyography (EMG) signals, but this only considers electrical responses and requires further validation. This study aims to simultaneously collect EMG and ultrasound (US) signals, extracting both electrical and mechanical responses of MU discharges, to validate their feasibility for MU tracking across movements. Methods: Ten able-bodied subjects participated in experiments involving isometric contraction of six hand movements. High-density surface EMG signals and ultrafast US images were concurrently recorded from the forearm muscles. The EMG signals were decomposed into MU spike trains and the separation vectors were kept for MU decoding across movements. The three-dimensional activation zone of each MU, including the action potentials on the skin surface and the twitch area in the muscle cross-sections, was extracted to validate the tracking performance. Main results: On average, 37 ± 17 MUs were identified from each decomposition, of which 20±16,2±2, and 2 ± 1 MUs were successfully tracked based on action potential, twitch area, and both, respectively. Conclusion and Significance: These results demonstrate strong evidence for the feasibility of tracking MUs using pre-trained separation vectors, supported by both electrical and mechanical responses. In addition, the study provides a benchmark to track MU activities across hand movements, extending the potential applications of neural decoding in neurophysiological investigation and human-machine interfacing. © 2025 Elsevier Ltd

关键词： Blind source separation Motor unit tracking Neural decoding Surface electromyography Ultrafast ultrasound

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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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