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arXiv 2025年

作者： Zhang, Chuhan Wang, Cong Pan, Wei Della Santina, Cosimo The Department of Cognitive Robotics Faculty of Mechanical Engineering Delft University of Technology Delft Netherlands The Department of Computer Science The University of Manchester Manchester United Kingdom

Inspired by the dynamic coupling of moto-neurons and physical elasticity in animals, this work explores the possibility of generating locomotion gaits by utilizing physical oscillations in a soft snake by means of a low-level spiking neural mechanism. To achieve this goal, we introduce the Double Threshold Spiking neuron model with adjustable thresholds to generate varied output patterns. This neuron model can excite the natural dynamics of soft robotic snakes, and it enables distinct movements, such as turning or moving forward, by simply altering the neural thresholds. Finally, we demonstrate that our approach, termed SpikingSoft, naturally pairs and integrates with reinforcement learning. The high-level agent only needs to adjust the two thresholds to generate complex movement patterns, thus strongly simplifying the learning of reactive locomotion. Simulation results demonstrate that the proposed architecture significantly enhances the performance of the soft snake robot, enabling it to achieve target objectives with a 21.6% increase in success rate, a 29% reduction in time to reach the target, and smoother movements compared to the vanilla reinforcement learning controllers or Central Pattern Generator controller acting in torque space. Copyright © 2025, The Authors. All rights reserved.

关键词： Neurons

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Co-state Neural Network for Real-time Nonlinear Optimal Control with Input Constraints

arXiv

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arXiv 2025年

作者： Lian, Lihan Inyang-Udoh, Uduak Department of Robotics University of Michigan Ann ArborMI United States Department of Mechanical Engineering University of Michigan Ann ArborMI United States

In this paper, we propose a method to solve nonlinear optimal control problems (OCPs) with constrained control input in real-time using neural networks (NNs). We introduce what we have termed co-state Neural Network (CoNN) that learns the mapping from any given state value to its corresponding optimal co-state trajectory based on the Pontryagin’s Minimum (Maximum) Principle (PMP). In essence, the CoNN parameterizes the Two-Point Boundary Value Problem (TPBVP) that results from the PMP for various initial states. The CoNN is trained using data generated from numerical solutions of TPBVPs for unconstrained OCPs to learn the mapping from a state to its corresponding optimal co-state trajectory. For better generalizability, the CoNN is also trained to respect the first-order optimality conditions (system dynamics). The control input constraints are satisfied by solving a quadratic program (QP) given the predicted optimal co-states. We demonstrate the effectiveness of our CoNN-based controller in a feedback scheme for numerical examples with both unconstrained and constrained control input. We also verify that the controller can handle unknown disturbances effectively. Copyright © 2025, The Authors. All rights reserved.

关键词： Quadratic programming

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Towards Biophysical Network Simulation of Stochastically-Formed Neurospheres 13th

Towards Biophysical Network Simulation of Stochastically-Fo...

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13th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2024

作者： Bennington, Michael J. Webster-Wood, Victoria A. Department of Mechanical Carnegie Mellon University PittsburghPA United States Department of Biomedical Engineering Carnegie Mellon University PittsburghPA United States McGowan Institute for Regenerative Medicine Carnegie Mellon University PittsburghPA United States Robotics Institute Carnegie Mellon University PittsburghPA United States

ISBN: (纸本)9783031725968

Biocomputing platforms, such as cultured neurospheres, have the potential to provide great advances in biohybrid computation and control systems. However, to design and fabricate neurospheres reliably and reproducibly, models that can accurately predict their computational behaviors are required. Towards the end of understanding how neurospheres perform higher-level computations, we present a model framework for simulating the dynamics of stochastically-connected neuron networks. Each neuron is modeled using biophysical models of neural excitability, and the system can be stimulated by a small number of simulated electrodes. The network response of the system is analyzed using Principal Components Analysis on the firing frequencies of the neurons. From preliminary simulations, we demonstrate the ability of these neurosphere networks to encode information about the magnitude of current stimuli. Future additions to this framework will incorporate the 3D geometry of both the neurosphere and individual dendritic trees. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Stochastic models

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Comparison of high temperature hot corrosion behavior of AlCoCrFeNiTi and AlCoCrFeNiZr high entropy alloy (HEAs) coatings

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Surface and Coatings Technology 2025年 511卷

作者： Odabas, Okan Ozgurluk, Yasin Karaoglanli, Abdullah Cahit Department of Mechanical Engineering Faculty of Engineering Architecture and Design Bartin74110 Turkey Program of Medical Services and Techniques Vocational School of Health Services Bartin University Bartin74100 Turkey Department of Metallurgical and Materials Engineering Faculty of Engineering Architecture and Design Bartin74110 Turkey

Composite coating technologies used in the aircraft industry are susceptible to hot corrosion damage caused by substandard fuels and harsh environmental conditions. In this context, it is crucial to evaluate the hot corrosion resistance of coating systems and to study the microstructural changes. Recent research has focused on the hot corrosion damage behavior of high entropy alloy (HEAs) coatings in the aircraft industry. In this study, two different HEA coating systems were designed by applying CoNiCrAlY powder, AlCoCrFeNiTi and AlCoCrFeNiZr HEA powders to an Inconel 718 substrate using two thermal spray coating techniques (high velocity oxy fuel (HVOF) and atmospheric plasma spray (APS)). Then, in order to investigate the microstructural changes in the coatings, a salt mixture of 45 % Na2SO4 and 55 % V2O5 was placed on the surface of the coatings and subjected to isothermal hot corrosion experiments at 900 °C for 1, 3, 5 and 10 h. Both coating systems exhibited outstanding stability, strength and increased corrosion resistance under high temperature, extremely corrosive conditions, and the damage effect in needle/rod-like hot corrosion was dominated by the formation of Co2VO4 compound as a corrosion product. © 2025 Elsevier B.V.

关键词： High temperature corrosion

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Correction: The green marine waste collector routing optimization with puma selectison-based neighborhood search algorithm

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Cluster Computing 2025年第3期28卷 1-2页

作者： Abdollahzadeh, Benyamin Javadi, Hatef Torağay, Oğuz Epicoco, Nicola Khodadadi, Nima Department of Mathematics Faculty of Science University of Hradec Králové Hradec Králové Czech Republic Department of Industrial Engineering Hacettepe University Ankara Turkey Leon Linton Department of Mechanical Robotics and Industrial Engineering Lawrence Technological University Southfield USA Department of Engineering LUM University Casamassima Italy Department of Civil and Architectural Engineering University of Miami Coral Gables USA

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Hierarchical Co3O4@ZnO binary oxide microstructures for high-performance photoelectrochemical glucose sensing

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Ceramics International 2025年

作者： Hilal, Muhammad Ali, Yasir Fayaz, Huma Cai, Zhicheng Kim, Hyojung Abdo, Hany S. Alnaser, Ibrahim A. Department of Semiconductor System Engineering Sejong University Seoul05006 Korea Republic of Department of Mechanical Robotics and Energy Engineering Dongguk University Seoul04620 Korea Republic of Deanship of Scientific Research King Saud University Riyadh11421 Saudi Arabia

Binary metal oxides with hierarchical architectures have emerged as promising platforms for non-enzymatic glucose sensing due to their tunable optoelectronic properties and intrinsic redox activity. In this work, we report a sustainable, additive-free synthesis of a 3D Co3O4@ZnO heterostructure via a one-pot hydrothermal method followed by inert-gas calcination, effectively minimizing oxygen interference and preserving structural integrity. The composite integrates the redox-rich, narrow-bandgap Co3O4 with UV-active, high-mobility ZnO to form a type-II heterojunction that enables broad-spectrum light absorption, efficient charge separation, and suppressed carrier recombination. These features also enhance the electrochemical behavior of the material, yielding an ultra-low charge transfer resistance (Rct = 3.35 Ω) and facilitating rapid electron transport and ion diffusion at the electrode/electrolyte interface. As a result, the Co3O4@ZnO heterostructure supports high-performance dual-mode glucose sensing under both dark and illuminated conditions. In the absence of light, the sensor exhibits a sensitivity of 114 μA cm−2 mM−1, a wide linear range (0.2–4 mM), and a fast response time (21 s). Upon illumination, a photoinduced internal electric field at the heterojunction interface significantly boosts performance, achieving a photoelectrochemical sensitivity of 231 μA cm−2 mM−1 with a rapid response of 11 s. Photocurrent studies further reveal response and recovery times of 5 s and 4 s, respectively. Importantly, the sensor also demonstrates reliable glucose detection in real urine samples, confirming its suitability for real-time physiological monitoring. These results highlight the Co3O4@ZnO heterostructure as an efficient and eco-friendly platform for stable, reliable, and high-performance dual-mode glucose sensing. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Redox reactions

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Investigation of lightweight pumice epoxy core woven banana fiber sandwich composites

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Polymer Composites 2025年

作者： Shahapurkar, Kiran Kiran, M.C. Chenrayan, Venkatesh Bhaviripudi, Vijayabhaskara Rao Tirth, Vineet Algahtani, Ali Department of Mechanical Engineering Alliance School of Applied Engineering Alliance University Bengaluru India Centre for Robotics Research Department of Mechanical Engineering Nitte Meenakshi Institute of Technology Bengaluru India Departamento de Física Facultidad de Ciencias Naturales Matemática y del Medio Ambiente Universidad Tecnológica Metropolitana Macul Santiago Chile Mechanical Engineering Department College of Engineering King Khalid University Abha Saudi Arabia Centre for Engineering and Technology Innovations King Khalid University Abha Saudi Arabia King Khalid University Abha Saudi Arabia

Substantial agricultural biomass possessing inherent potential for lignocellulosic fiber is discarded as waste post-harvest in developing nations. Natural fibers are the right candidate to replace the synthetic ones to promote a sustainable economy and green environment. The present study concentrates on the fabrication of a core of lightweight pumice particles interspersed among woven banana fiber composites. Epoxy cores were produced by altering the quantity of pumice content (2.5, 5, 7.5, and 10 wt.%) while maintaining a constant woven banana fiber content of 40 wt.%. Composites were processed via the hand layup method. The objective of the effort is to improve the performance of composites by utilizing the distinct qualities of pumice, hence customizing the characteristics of the composite material to satisfy particular application demands. The tensile and flexural qualities improve with an increase in pumice content in the core, suggesting the advantageous effects of reinforcing pumice to boost the properties. The scanning electron micrographs are analyzed to comprehend the microstructure and its influence on the characteristics. The numerical simulation results are employed to corroborate the study's conclusions. The numerical results align well with experimental observations, exhibiting a 3% reduction in accuracy. Highlights: Sandwich composites fabricated with pumice/epoxy core and woven banana fibers. Tensile and flexural characteristics are examined and simulated. Pumice affects the flexural and tensile characteristics of composites. Flexural modulus and strength exhibit considerable improvement with an increase in pumice content. © 2025 Society of Plastics Engineers.

关键词： Fruits

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Electric Vehicle Charging Demand Prediction using Multiresolution Sinusoidal Neural Network Optimized with Addax Optimization

Electric Vehicle Charging Demand Prediction using Multiresol...

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Trends in Material Science and Inventive Materials (ICTMIM), International Conference on

作者： Rajesh Munirathnam Rohit P. Jadhav Nilesh M. Mahajan Amit Barve M. E. Shashi Kumar Natrayan L Data & Analytics Division TechnoGen Inc Hillsborough New Jersey USA Department of Robotics and Automation D.Y. Patil College of Engineering Akurdi Pune Maharashtra Department of Computer Science and Engineering Parul Institute of Technology Faculty of Engineering and Technology Parul University Limda Gujarat Department of Mechanical Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru Karnataka Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai Tamil Nadu

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

Electric Vehicle (EV) charging demand prediction, while essential for optimizing charging infrastructure and energy management, faces challenges such as data inaccuracies and uncertainties in user behavior patterns. These issues define inaccurate demand forecasts which cause the wrong placement of charging stations and distribution of energy. Also, as the pattern of the EV charging is not static may change due to many factors such as climate, time of day, price preference among others, the prediction models may not handle the dynamism and hence lower the reliability of the forecast results. To overcome these drawbacks, this manuscript proposes an efficient approach for EV charging demand prediction. The data is gathered from a dataset on EV charging. The data is then sent to pre-processing. Using the Maximum Correntropy Quaternion Kalman Filter (MCQKF), the pre-processing section eliminates missing values and normalizes the input. To forecast EV charging demand, the Multiresolution Sinusoidal Neural Network (MSNN) receives the results of the pre-processing data. MSNN’s weight parameter is optimized using Addax Optimization (AO). The proposed MSNN-AO is utilized within the MATLAB platform. The proposed MSNN-AO technique is compared with the existing techniques such as Long Short-Term Memory Neural Network (LSTMNN), Heterogeneous Spatial-Temporal Graph Convolutional Network (HSTGNN) and Artificial Neural Networks (ANN), respectively. The MSNN-AO method achieves an accuracy of 97%, precision of 95%, and a Root Mean Square Error (RMSE) of 2.2%, demonstrating its superior performance in predicting EV charging demand. This highlights the proposed method’s effectiveness in minimizing prediction errors, reducing RMSE by 22.36%, and improving precision by 14.89% compared to existing methods. The MSNN-AO method’s higher accuracy and precision, coupled with its robust performance, make it a reliable and efficient solution for EV charging demand forecasting.

关键词： Accuracy Uncertainty Quaternions Energy resolution Electric vehicle charging Reliability Kalman filters Spatial resolution Root mean square Optimization

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A Study on Impact-Aware Aerial Robots Colliding with the Environment at Non-Vanishing Speed

A Study on Impact-Aware Aerial Robots Colliding with the Env...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Gayatri Indukumar Alessandro Saccon Antonio Franchi Chiara Gabellieri Robotics and Mechatronics Department Electrical Engineering Mathematics and Computer Science (EEMCS) Faculty University of Twente Enschede The Netherlands Department of Mechanical Engineering Eindhoven University of Technology Eindhoven The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Enabling aerial robots to handle dynamic contacts happening at non-vanishing speeds can enlarge the range of their applications. In this work, we propose an impactaware strategy to allow aerial multirotor robots to recover from impacts. The method leverages a reactive strategy not requiring low-level changes to the motion controller commonly implemented onboard quadrotors, which might be not viable or not desirable for most users. Extensive simulation tests show that the proposed strategy considerably increases the tolerated velocity at impact in tasks in which the robot either picks an object up or collides against an object to clear its way. Preliminary experimental results using Crazyflie UAVs are also presented.

关键词： Trajectory tracking Dynamics Lead Autonomous aerial vehicles Stability analysis Robustness Computer crashes Trajectory Robots Quadrotors

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Ultrafast, High-Intensity Laser Material Interaction in Polycrystalline Alumina Transparent Ceramics

SSRN

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SSRN 2025年

作者： Chong, Poh Yin Wu, Xingzhong Castillo, Gabriel R. Garay, Javier E. Laboratory Mechanical and Aerospace Engineering Department Materials Science and Engineering Program University of California La Jolla San DiegoCA92093 United States

High-intensity pulsed laser-material interaction is a complicated process involving various laser parameters and material properties, and the coupling of these factors affects material modifications. This study investigates the laser-material interactions of single-crystal alumina (SCA) and transparent polycrystalline alumina (PCA). To understand the underlying mechanism of laser-induced modifications, single-shot irradiations are conducted using an ultrafast laser (λ = 1030 nm, τρ = 490 fs). This experiment focuses on the high-intensity regime from 1012 W/cm2 to 1015 W/cm2, generating high temperatures and pressure causing modifications (melting, ablation, and fracture). While SCA and PCA are fundamentally Al2O3, the difference in microstructure alters the optical and mechanical properties. The ablation depth shows a sublinear power law relationship with laser intensity for both materials although the energy dependence is lower for PCA. The differences can be attributed to different damage mechanisms;the laser-induced craters in SCA exhibit predominantly melting whereas PCA demonstrates fracture-like morphologies. The fracture in PCA is surprising given its higher indent-produced fracture resistance. The differences in fracture behavior can be reconciled considering the much higher pressure application rates produced by laser pulsing. PCA has a lower laser-induced damage threshold (LIDT) than SCA. Laser-induced crater area and volume increase linearly with laser fluence and peak intensity. Altering the focusing conditions can change the LIDT and expand the laser processing window. © 2025, The Authors. All rights reserved.

关键词： Single crystals

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