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Enhanced corrosion resistance of laser powder bed fusion 316L stainless steel by modifying the microstructure through heat treatment

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Journal of Materials Research and Technology 2025年 36卷 7158-7171页

作者： Cuiling Zhao Yuchao Bai Qi Yan Bing Li Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robots Harbin Institute of Technology Shenzhen 518055 China Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong Harbin Institute of Technology Shenzhen 518055 China School of Robotics and Advanced Manufacture Harbin Institute of Technology Shenzhen 518055 China Department of Mechanical Engineering College of Design and Engineering National University of Singapore Singapore 117575 Singapore

This study aims to investigate the microstructural evolution of laser powder bed fusion (LPBF) 316L stainless steel during heat treatment and its effect on corrosion resistance through microstructural characterization and corrosion testing. The results show that the as-built LPBF samples featured melt pool boundaries, cellular structures, a few nano-sized manganese silicate particles and irregular grains with strong fiber texture <101>, which are retained after heat treatment at 450 °C. With temperature increase to 850 °C, a σ phase rich in Cr, Mo, and S elements was formed. Subsequently, after heat treatment at 1100 °C, melt boundary disappears and large square grains similar to the cast counterparts appear. Electrochemical tests demonstrate that the corrosion resistance of LPBF samples surpasses the cast samples heat treated at 1100 °C. In addition, annealing at or below 1100 °C will reduce the corrosion resistance of LPBF samples due to the formation of hazardous precipitates. However, after heat treatment at 1300 °C, the best corrosion resistance was obtained due to the diffusion of Cr, Mo and S elements into the matrix and homogeneous microstructure. This study provides a method for effectively improving the corrosion resistance of LPBF 316L stainless steel and understanding the corresponding corrosion mechanism.

关键词： Laser powder bed fusion Corrosion behaviour Heat treatment 316L stainless steel Microstructure

SAF: Local Shape-aware Face-based Garment Collision Handling via Neural SDFs

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SAF: Local Shape-aware Face-based Garment Collision Handling...

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Minzhe Tang Ruisheng Yuan Dongliang Kou Mingyang Sun Lihua Zhang Academy for Engineering and Technology Fudan University Shanghai China Institute of Metaverse & Intelligent Medicine Fudan University Shanghai China Jilin Provincial Key Laboratory of Intelligence Science and Engineering Changchun China Engineering Research Center of AI and Robotics Ministry of Education Shanghai China AI and Unmanned Systems Engineering Research Center of Jilin Province Changchun China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Learning-based garment prediction presents an appealing alternative to physics-based methods owing to its high efficiency. However, the predicted garments can exhibit noticeable penetrations into the body. Many collision-handling methods operate in the point domain, which has an inherent limitation in addressing the penetration issues with the mesh faces. In light of this, we propose a local Shape-Aware, Face-based collision handling approach (SAF) that can be applied to garment prediction networks to achieve real-time collision handling. Considering the nature of garments, we design a compact formulation to model the continuity of the garment surface, and utilize neural Signed Distance Fields (SDFs) to accomplish penetration resolution. Recognizing the significant impact of the body’s local shape on collision handling, we further propose using the angles between SDF gradients to characterize the sharpness of the body. Our approach can compensate for the inaccuracy of neural SDFs and preserve local smoothness and details. Extensive experiments demonstrate the outstanding performance and generalizability of our method.

关键词： Shape Face recognition Clothing Signal processing Real-time systems Acoustics Character recognition Speech processing Faces

BloomScene: Lightweight Structured 3D Gaussian Splatting for Crossmodal Scene Generation

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arXiv 2025年

作者： Hou, Xiaolu Li, Mingcheng Yang, Dingkang Chen, Jiawei Qian, Ziyun Zhao, Xiao Jiang, Yue Wei, Jinjie Xu, Qingyao Zhang, Lihua Academy for Engineering and Technology Fudan University China Institute of Metaverse & Intelligent Medicine Fudan University China Engineering Research Center of AI and Robotics Ministry of Education China Jilin Provincial Key Laboratory of Intelligence Science and Engineering China Artificial Intelligence and Unmanned Systems Engineering Research Center of Jilin Province China ByteDance Inc China

With the widespread use of virtual reality applications, 3D scene generation has become a new challenging research frontier. 3D scenes have highly complex structures and need to ensure that the output is dense, coherent, and contains all necessary structures. Many current 3D scene generation methods rely on pre-trained text-to-image diffusion models and monocular depth estimators. However, the generated scenes occupy large amounts of storage space and often lack effective regularisation methods, leading to geometric distortions. To this end, we propose BloomScene, a lightweight structured 3D Gaussian splatting for crossmodal scene generation, which creates diverse and high-quality 3D scenes from text or image inputs. Specifically, a crossmodal progressive scene generation framework is proposed to generate coherent scenes utilizing incremental point cloud reconstruction and 3D Gaussian splatting. Additionally, we propose a hierarchical depth prior-based regularization mechanism that utilizes multi-level constraints on depth accuracy and smoothness to enhance the realism and continuity of the generated scenes. Ultimately, we propose a structured context-guided compression mechanism that exploits structured hash grids to model the context of unorganized anchor attributes, which significantly eliminates structural redundancy and reduces storage overhead. Comprehensive experiments across multiple scenes demonstrate the significant potential and advantages of our framework compared with several baselines. Copyright © 2025, The Authors. All rights reserved.

关键词： Virtual reality

Towards Open-Source and Modular Space systems with ATMOS

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arXiv 2025年

作者： Roque, Pedro Phodapol, Sujet Krantz, Elias Lim, Jaeyoung Verhagen, Joris Jiang, Frank J. Dörner, David Mao, Huina Tibert, Gunnar Siegwart, Roland Stenius, Ivan Tumova, Jana Fuglesang, Christer Dimarogonas, Dimos V. Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden School of Engineering Sciences KTH Royal Institute of Technology Stockholm Sweden Autonomous Systems Laboratory ETH Zürich Zürich Switzerland Division of Robotics Perception and Learning KTH Royal Institute of Technology Stockholm Sweden

In the near future, autonomous space systems will compose many of the deployed spacecraft. Their tasks will involve autonomous rendezvous and proximity operations with large structures, such as inspections, assembly, and maintenance of orbiting space stations, as well as human-assistance tasks over shared workspaces. To promote replicable and reliable scientific results for autonomous control of spacecraft, we present the design of a space robotics laboratory based on open-source and modular software and hardware. The simulation software provides a software-in-the-loop architecture that seamlessly transfers simulated results to the hardware. Our results provide an insight into such a system, including comparisons of hardware and software results, as well as control and planning methodologies for controlling free-flying platforms. Copyright © 2025, The Authors. All rights reserved.

关键词： Space stations

Collision-Aware MPCC Integrated with Neural Augmentation for Quadrotor Trajectory Tracking

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Collision-Aware MPCC Integrated with Neural Augmentation for...

International Conference on Mechatronics (ICM)

作者： Chuanqi Hu Jin Wang Yikai Chen Yonghang Chen Zhi Zheng Jun Meng Guodong Lu Polytechnic Institute Zhejiang University Hangzhou China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou China Zhejiang Key Laboratory of Industrial Big Data and Robot Intelligent Systems Zhejiang University Hangzhou China Robotics Research Center of Yuyao City Ningbo China School of Mechanical Engineering Zhejiang University Hangzhou China National Elite Institute of Engineering Chongqing University Chongqing China College of Electrical Engineering Zhejiang University Hangzhou China Center for Data Mining and Systems Biology College of Electrical Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798331533892

ISBN: (纸本)9798331533908

This paper presents a trajectory tracking algorithm designed for autonomous quadrotors to navigate complex dy-namic environments that is resilient to collision disturbances. Since it combines Model Predictive Contouring Control (MPCC) with the capabilities of neural networks, our method is named MPCC Integrated with Neural Augmentation (MINA). By equip-ping the quadrotor with PVDF piezoelectric sensors, we achieve real-time perception of collision forces and utilize S4D-Conv Adaptive Net Architecture (SANA) for state computation, a network that integrates the advantages of S4D and convolutional kernels to enhance the accuracy of state predictions. We incorporate the predicted results into the MPCC framework to optimize the thrust output of the quadrotor for the next time step, ensuring precise trajectory tracking. Experimental validation demonstrates the reliability and effectiveness of our algorithm, providing an innovative solution for autonomous flight and trajectory tracking of quadrotors in complex dynamic environments.

关键词： Trajectory tracking Navigation Heuristic algorithms Neural networks Reliability theory Predictive models Prediction algorithms Real-time systems Sensors Quadrotors

Toward Dynamic Control of Tendon-Driven Continuum Robots using Clarke Transform

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arXiv 2025年

作者： Muhmann, Christian Grassmann, Reinhard M. Bartholdt, Max Burgner-Kahrs, Jessica Continuum Robotics Laboratory Department of Mathematical and Computational Sciences University of Toronto MississaugaONL5L 1C6 Canada Institute of Mechatronic Systems Faculty of Mechanical Engineering Leibniz University Hannover Garbsen30823 Germany

In this paper, we propose a dynamic model and control framework for tendon-driven continuum robots with multiple segments and an arbitrary number of tendons per segment. Our approach leverages the Clarke transform, the Euler-Lagrange formalism, and the piecewise constant curvature assumption to formulate a dynamic model on a two-dimensional manifold embedded in the joint space that inherently satisfies tendon constraints. We present linear controllers that operate directly on this manifold, along with practical methods for preventing negative tendon forces without compromising control fidelity. We validate these approaches in simulation and on a physical prototype with one segment and five tendons, demonstrating accurate dynamic behavior and robust trajectory tracking under real-time conditions. Copyright © 2025, The Authors. All rights reserved.

关键词： Linear control systems

Bioinspired Sensing of Undulatory Flow Fields Generated by Leg Kicks in Swimming

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arXiv 2025年

作者： Wang, Jun Shen, Tongsheng Zhao, Dexin Zhang, Feitian Department of Advanced Manufacturing and Robotics The State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University Beijing100871 China The National Innovation Institute of Defense Technology Beijing China National Innovation Institute of Defense Technology Beijing100071 China

The artificial lateral line (ALL) is a bioinspired flow sensing system for underwater robots, comprising of distributed flow sensors. The ALL has been successfully applied to detect the undulatory flow fields generated by body undulation and tail-flapping of bioinspired robotic fish. However, its feasibility and performance in sensing the undulatory flow fields produced by human leg kicks during swimming has not been systematically tested and studied. This paper presents a novel sensing framework to investigate the undulatory flow field generated by swimmer’s leg kicks, leveraging bioinspired ALL sensing. To evaluate the feasibility of using the ALL system for sensing the undulatory flow fields generated by swimmer leg kicks, this paper designs an experimental platform integrating an ALL system and a lab-fabricated human leg model. To enhance the accuracy of flow sensing, this paper proposes a feature extraction method that dynamically fuses time-domain and time-frequency characteristics. Specifically, time-domain features are extracted using one-dimensional convolutional neural networks and bidirectional long short-term memory networks (1DCNN-BiLSTM), while time-frequency features are extracted using short-term Fourier transform and two-dimensional convolutional neural networks (STFT-2DCNN). These features are then dynamically fused based on attention mechanisms to achieve accurate sensing of the undulatory flow field. Furthermore, extensive experiments are conducted to test various scenarios inspired by human swimming, such as leg kick pattern recognition and kicking leg localization, achieving satisfactory results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convolutional neural networks

Wearable Fiber Bragg Grating Sensors for Physiological Signal and Body Motion Monitoring: A Review

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Zhang, Feng Hao, Yupeng Tian, Aofei Yang, Zhengbao Zhang, Bo Fukuda, Toshio Shi, Chaoyang Tianjin University Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education School of Mechanical Engineering Tianjin300072 China The Hong Kong University of Science and Technology Department of Mechanical and Aerospace Engineering Hong Kong Future Robotics Organization Waseda University Tokyo162-0044 Japan Nagoya University Department of Micro-Nano Systems Engineering Aichi Nagoya464-8601 Japan

Wearable sensors play a crucial role in real-time physiological parameters and body motion monitoring, enabling early detection and prevention of potential health issues. However, conventional electrical sensors are susceptible to electromagnetic interference (EMI), limiting their application in magnetic resonance imaging (MRI), electrosurgery, and humid environments. Optical wearable devices based on fiber Bragg gratings (FBGs) offer distinct advantages such as miniaturization, immunity to EMI, high sensitivity, and multiplexing capabilities, making them promising for healthcare applications. Nevertheless, FBG sensors face challenges such as susceptibility to breakage and cross-sensitivity to temperature and multiple strain signals, creating obstacles in expanding strain monitoring range, reducing monitoring errors, and improving wear resistance. This review comprehensively introduces the latest advancements, technical challenges, and potential solutions associated with wearable FBG sensing devices for detecting physiological signals and body motion, particularly emphasizing their applications in monitoring small- and large-strain body movements. This article focuses on the sensing characteristics of FBG units in both soft and rigid substrate materials and tracks the advancement in sensing structure optimization for enhanced measurement capabilities. Future directions and opportunities for technological improvement in this field are also discussed. © 1963-2012 IEEE.

关键词： Fiber Bragg gratings

Correction of measurement accuracy for optical measuring machines depending on the direction vector of the point

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Measurement: Sensors 2025年

作者： Harmatys, Wiktor Gąska, Adam Gąska, Piotr Gruza, Maciej Laboratory of Coordinate Metrology Cracow University of Technology al. Jana Pawla II 37 Cracow31-864 Poland Department of Manufacturing Systems Faculty of Mechanical Engineering and Robotics AGH University of Krakow al. Mickiewicza 30 Krakow30-059 Poland

Optical measurement techniques are one of the most frequently used coordinate measurement systems in factory conditions. Due to their continuous development and miniaturization, this allowed them to be installed in various types of coordinate measuring machines, as a result of which, the machine equipped with a classic contact head and an optical head enables multi-sensor measurement. The growing popularity of optical heads is due to the fact that they enable non-contact measurement of even small and sensitive objects, which in many cases is impossible to do with a contact head. In addition, they owe their popularity to the fact that a significantly smaller number of precise mechanical and electronic elements are used in their construction. Another advantage is that they enable collecting a large number of points in a short time, which is more difficult with traditional contact systems, and with the development of these techniques, optical heads offer increasingly higher accuracy. However, the disadvantage of this method is that the stability and accuracy of measurements using this method depend on a large number of factors, including: lighting conditions, quality of measured surface and its reflectivity. Another problem that has not been fully solved is the lack of direct correlation between contact and non-contact measurements due to the fact that it is very difficult to obtain a measurement of exactly the same point using these two measurement techniques. Another problem related to the measurement accuracy of this type of measuring heads, especially for the end user, is that the metrological software of most manufacturers is closed software, i.e. no one other than the manufacturer has access to the source code and therefore the techniques and algorithms for detecting a point in the image are known only to the manufacturer. Due to the fact that different algorithms may detect a point in the image in a different way, especially if the direction vector is not fully

关键词： Coordinate measuring machines