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arXiv 2023年

作者： Gabellieri, C. Tognon, M. Sanalitro, D. Franchi, A. Robotics and Mechatronics Group EEMCS Faculty University of Twente Enschede Netherlands Inria Univ Rennes CNRS IRISA Campus de Beaulieu Rennes35042 Cedex France LAAS-CNRS Université de Toulouse CNRS Toulouse France Department of Computer Control and Management Engineering Sapienza University of Rome Rome00185 Italy

This work studies how parametric uncertainties affect the cooperative manipulation of a cable-suspended beam-shaped load by means of two aerial robots not explicitly communicating with each other. In particular, the work sheds light on the impact of the uncertain knowledge of the model parameters available to an established communication-less force-based controller. First, we find the closed-loop equilibrium configurations in the presence of the aforementioned uncertainties, and then we study their stability. Hence, we show the fundamental role played in the robustness of the load attitude control by the internal force induced in the manipulated object by non-vertical cables. Furthermore, we formally study the sensitivity of the attitude error to such parametric variations, and we provide a method to act on the load position error in the presence of the uncertainties. Eventually, we validate the results through an extensive set of numerical tests in a realistic simulation environment including underactuated aerial vehicles and sagging-prone cables, and through hardware experiments. Copyright © 2023, The Authors. All rights reserved.

关键词： Cables

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Direct LiDAR-Inertial Odometry: Lightweight LIO with Continuous-Time Motion Correction

arXiv

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arXiv 2022年

作者： Chen, Kenny Nemiroff, Ryan Lopez, Brett T. The Department of Electrical and Computer Engineering University of California Los Angeles Los AngelesCA United States The Department of Mechanical and Aerospace Engineering University of California Los Angeles Los AngelesCA United States The Verifiable and Control-Theoretic Robotics Laboratory University of California Los Angeles Los AngelesCA United States

Aggressive motions from agile flights or traversing irregular terrain induce motion distortion in LiDAR scans that can degrade state estimation and mapping. Some methods exist to mitigate this effect, but they are still too simplistic or computationally costly for resource-constrained mobile robots. To this end, this paper presents Direct LiDAR-Inertial Odometry (DLIO), a lightweight LiDAR-inertial odometry algorithm with a new coarse-to-fine approach in constructing continuous-time trajectories for precise motion correction. The key to our method lies in the construction of a set of analytical equations which are parameterized solely by time, enabling fast and parallelizable point-wise deskewing. This method is feasible only because of the strong convergence properties in our nonlinear geometric observer, which provides provably correct state estimates for initializing the sensitive IMU integration step. Moreover, by simultaneously performing motion correction and prior generation, and by directly registering each scan to the map and bypassing scan-to-scan, DLIO's condensed architecture is nearly 20% more computationally efficient than the current state-of-the-art with a 12% increase in accuracy. We demonstrate DLIO's superior localization accuracy, map quality, and lower computational overhead as compared to four state-of-the-art algorithms through extensive tests using multiple public benchmark and self-collected datasets. Copyright © 2022, The Authors. All rights reserved.

关键词： State estimation

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Propagating beams carrying orbital angular momentum through simulated optical turbulence generated by Rayleigh–Bénard natural convection

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Waves in Random and Complex Media 2023年

作者： Avramov-Zamurovic, S. Judd, K.P. Matt, S. Handler, R.A. Watnik, A.T. Lindle, J.R. Esposito, J.M. Jarrett, W.A. Weapons Robotics and Control Engineering Department United States Naval Academy AnnapolisMD United States United States Naval Research Laboratory WashingtonDC United States Ocean Sciences Division US Naval Research Laboratory John C. Stennis Space Center MS United States Department of Mechanical Engineering George Mason University FairfaxVA United States DCS Corp AlexandriaVA United States

Numerical simulations of Rayleigh–Bénard (RB) convective flow are performed to determine the optical and mechanical turbulence properties and resulting index of refraction field in order to study the propagation characteristics of a laser beam carrying orbital angular momentum. The simulations are carried out in air using a computational fluid dynamics package which solves the Navier-Stokes equations. The computational domain is 0.1 m × 0.5 m × 0.5 m with a temperature difference of 1°K maintained between the top and bottom plate. The simulated temperature field is then converted into refractive index values. To study light propagation through the turbulent volume the split-step screen method is employed with screens at 0.025 m distance from each other along the propagation path which ranges from 0.5 m to 2.5 m. The structure of the phase screens, their spatio-temporal correlation with respect to up/down drafts, and phase changes across regions of interest are discussed. It was observed as the propagation distance increased, the orbital angular momentum carrying Laguerre–Gaussian beams wandered and the beam phase singularity distorted thus impacting the light intensity distribution. In addition, it was found that higher topological charge and order of Laguerre polynomial result in increased distortion of the beam vortex. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Laser beams

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In-Situ Sensing and Dynamics Predictions for Electrothermally-Actuated Soft Robot Limbs

arXiv

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arXiv 2021年

作者： Sabelhaus, Andrew P. Mehta, Rohan Wertz, Anthony T. Majidi, Carmel Soft Robotics Control Lab Department of Mechanical Engineering Boston University BostonMA United States Soft Machines Lab Department of Mechanical Engineering Carnegie Mellon University PittsburghPA United States Robotics Institute Carnegie Mellon University PittsburghPA United States

Untethered soft robots that locomote using electrothermally-responsive materials like shape memory alloy (SMA) face challenging design constraints for sensing actuator states. At the same time, modeling of actuator behaviors faces steep challenges, even with available sensor data, due to complex electrical-thermal-mechanical interactions and hysteresis. This article proposes a framework for in-situ sensing and dynamics modeling of actuator states, particularly temperature of SMA wires, which is used to predict robot motions. A planar soft limb is developed, actuated by a pair of SMA coils, that includes compact and robust sensors for temperature and angular deflection. Data from these sensors are used to train a neural network based on the long short-term memory (LSTM) architecture to model both unidirectional (single SMA) and bidirectional (both SMAs) motion. Predictions from the model demonstrate that data from the temperature sensor, combined with control inputs, allow for dynamics predictions over extraordinarily long open-loop timescales (10 minutes) with little drift. Prediction errors are on the order of the soft deflection sensor’s accuracy. This architecture allows for compact designs of electrothermally-actuated soft robots that include sensing sufficient for motion predictions, helping to bring these robots into practical application. Copyright © 2021, The Authors. All rights reserved.

关键词： Forecasting

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Reinforcement Learning with Large Language Model for Hybrid Disassembly Lines in Remanufacturing Contexts

Reinforcement Learning with Large Language Model for Hybrid ...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Peng Ji Xi Wang Guo Jiacun Wang Weitian Wang Shu Jin Qin Ying Tang Qi Kang College of Information and Control Engineering Liaoning Petrochemical University Fushun China Dept of Comp. Sci. and Soft. Eng. Monmouth University W. Long Branch NJ USA Collaborative Robotics and Smart Systems Laboratory (CRoSS Lab) Montclair State University Montclair NJ USA College of Economics and Management Shangqiu Normal University Shangqiu China Electrical and Computer Engineering Rowan University Glassboro New Jersey USA Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Large language models (LLM), ChatGPT is making substantial impact across various fields. This study for the first time presents a novel approach to the hybrid disassembly line balancing problem using LLM and reinforcement learning algorithms in remanufacturing contexts. The problem is divided into two sub-stages. LLM is innovatively used to capture a disassembly sequence well in the first stage, while reinforcement learning is utilized to address the problem in the second stage. Upon comparing the performance with and without LLM, the proposed approach significantly reduces the trial-and-error space and achieves faster convergence to achieve the desired solution. Future work of this study is also discussed.

关键词： Computer aided software engineering Automation Large language models Reinforcement learning Chatbots Convergence

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Printability and properties of PSNZT piezoelectric ceramics fabricated by DLP additive manufacturing

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Ceramics International 2025年

作者： Yu, Mengyuan Fan, Guifen Li, Yingkang Ling, Xile Gong, Feng Liu, Gang Bai, Jiaming Li, Mantian Zhou, Peng Zhang, Dongyang Sun, Lining Hubei Key Laboratory of Plasma Chemistry and Advanced Materials School of Materials Science and Engineering Wuhan Institute of Technology Wuhan430205 China Institute of Intelligent Manufacturing Technology Shenzhen Polytechnic University Shenzhen518055 China MOE Huazhong University of Science and Technology Wuhan430074 China Department of Mechanical and Electronic Engineering College of Mechatronics and Control Engineering Shenzhen University Shenzhen518055 China Shenzhen Blueswin Industrial Co. Ltd Shenzhen518117 China Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen518055 China Institute of Critical Materials for Integrated Circuits Shenzhen Polytechnic University Shenzhen518055 China Robotics and Microsystems Center School of Mechanical and Electric Engineering Soochow University Suzhou215021 China

Achieving the synergy of low viscosity, high printing precision and enhanced curing ability for lead zirconate titanate (PZT) components is a critical issue in the field of digital light processing (DLP). Herein, the effect of calcination temperature on the morphology and grain size of PSNZT [(Pb0.92Sr0.08)(Zr0.533Ti0.443Nb0.024)O3]ceramic powder has been investigated, and a lowest viscosity, higher printing precision and enhanced curing ability of PSNZT ceramic slurry has been achieved, resulting in a high piezoelectric constant (d33 = 379pC/N) and a high dielectric constant (Εr = 1308@100 KHz) via DLP process combined with following sintering densification (1220 °C/3 h). © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Piezoelectric ceramics

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GCNPMDA: Human Microbe-Disease Association Prediction by Hirarchical Graph Convolutional Network with Layer Attention

SSRN

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SSRN 2024年

作者： Wu, Chuanyan Lin, Bentao Zhang, Huanghe Xu, Da Gao, Rui Song, Rui Liu, Zhi-Ping De Marinis, Yang School of Intelligent Engineering Shandong Management University No.3500 Dingxiang Road Shandong Jinan250357 China School of Control Science and Engineering Shandong University No.17923 Jingshi Road Shandong Jinan250061 China Center for Robotics School of Control Science and Engineering Shandong University No.17923 Jingshi Road Shandong Jinan250061 China School of Mathematics Science Liaocheng University No.1 Hunan Road Dongchangfu District Shandong Liaocheng252000 China Department of Clinical Sciences Lund University Solvegatan 19 Skaane Malmo22184 Sweden Oxford Centre for Diabetes Endocrinology & Metabolism Radcliffe Department of Medicine University of Oxford Old Road OxfordOX3 7LE United Kingdom

Microorganisms play a crucial role in various physiological processes. Changes in microbial communities can serve as potential biomarkers for diseases. However, the association between microorganisms and diseases is still unclear. In this paper, we introduce a novel computational model, the Graph Convolutional Network to Predict Microbe-Disease Associations (GCNPMDA), which employs layer attention mechanisms (see Figure 1). GCNPMDA integrates known microbe-disease associations, microbe-microbe similarities, and disease-disease similarities into a heterogeneous network. The model utilizes a Graph Convolutional Network (GCN) to learn embeddings for diseases and microbes. To enhance attribute information, microbe-microbe similarities are computed using Cosine similarity, Jaccard similarity, Gaussian kernel, and functional information, while disease-disease similarities are computed using Cosine similarity, Jaccard similarity, Gaussian kernel, and symptom information. Additionally, attention mechanisms are applied to combine embeddings from multiple graph convolution layers. The model's predictive effectiveness is evaluated on Human Microbe-Disease Association Database (HMDAD). Leave-one-out cross-validation (LOOCV) was conducted. The Area Under ROC Curve (AUC) of LOOCV is 0.98. The 5-fold cross-validation (5-fold CV) on HMDAD yields average AUC of 0.98 ± 0.009. Furthermore, we carried out a case study of type 2 diabetes (T2D), inflammatory bowel disease (IBD), and rheumatoid arthritis. Based on existing literature evidence, it was confirmed that 6, 7, and 7 of the top-10 inferred microbes have established associations with T2D, IBD, and rheumatoid arthritis, respectively. GCNPMDA demonstrates potential efficacy in identifying disease-related microbes, offering a promising tool to uncover the intricate relationship between microorganisms and their human hosts. © 2024, The Authors. All rights reserved.

关键词： Forecasting

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control of a Class of Underactuated Systems by Successive Submanifold Stabilization ⁎

引用

IFAC-PapersOnLine 2021年第19期54卷 352-358页

作者： Fabian Beck Noboru Sakamoto Christian Ott Institute of Robotics and Mechatronics German Aerospace Center (DLR) 82234 Wessling Germany Department of Mechanical Engineering and System Control Nanzan University Yamzato-cho 18 Showa-ku Nagoya 466-8673 Japan

Many control design methods for underactuated systems require solving a partial differential equation, which can be complex for systems with many degrees of freedom. In order to reduce the complexity, it is proposed to decompose the dynamics into several subsystems. The problem then reduces to the successive stabilization of the individual subsystems, i.e., each step is a submanifold stabilization problem of reduced dimension. In this way, control methods which are only practicable for lower dimensional systems can be applied to the overall complex dynamical system. To ensure that the subsystems can be stabilized independently, the dynamics are transformed by a change of coordinates to a form with block-diagonal inertia metric. For the unactuated part kinetic symmetries can be utilized, whereas for the actuated part null space projectors are employed to decouple the dynamics with respect to the inertia metric. The subsystems are then stabilized by optimal control or PD-like feedback. In the stability analysis semidefinite Lyapunov functions are employed. The procedure is demonstrated for a manipulator on an elastic base and validated in simulation.

关键词： Hamiltonian dynamics robotics Nonlinear control

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Fabrication grammars: bridging design and robotics to control emergent material expressions

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Construction robotics 2021年第1期5卷 35-48页

作者： Iremnur Tokac Johan Philips Herman Bruyninckx Andrew Vande Moere Design Department of Architecture KU Leuven Leuven Belgium Robotics Automation and Mechatronics Department of Mechanical Engineering KU Leuven Leuven Belgium Flanders Make@KU Leuven Core Lab ROB Heverlee Belgium Control Systems Technology Department of Mechanical Engineering Technical University Eindhoven Eindhoven Netherlands

Designers physically engage with a material to experience how certain characteristics allow the fabrication of unique expressions. In digital fabrication, however, this improvisational negotiation is typically replaced by a virtual simulation that predicts how a material expression can be fabricated, limiting the resulting design language to algorithmic forms. In contrast, we believe that digital fabrication can also produce ‘emergent’ material expressions that are so confounded that they appear slightly differently even when being produced by identical operations. This paper argues that such expressions can be executed by a domain-driven feedback paradigm, which integrates a human-in-the-loop to encode the tacit fabrication knowledge that is generated by reviewing intermediate outcomes. We encode this tacit knowledge by fabrication grammars, rule-based descriptions that causally relate fabrication parameters to qualitative descriptions of material expressions. By documenting a set of Single Point Incremental Forming experiments, this paper demonstrates how emergent material expressions can be controlled by semantically meaningful fabrication grammars, which even can be combined towards purposeful design goals. We believe our findings might allow the digital fabrication of material expressions that appear to have been produced manually or naturally; and support the future sharing of tacit fabrication knowledge.

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Customizable Inverse Sensor Model for Bayesian and Dempster-Shafer Occupancy Grid Frameworks 20th

Customizable Inverse Sensor Model for Bayesian and Dempster-...

引用

20th Polish control Conference, PCC 2020

作者： Porębski, Jakub Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Automatic Control and Robotics AGH University of Science and Technology Kraków Poland Aptiv Services Poland S.A. Kraków Poland

ISBN: (纸本)9783030509354

Occupancy grid mapping is an important component in a road scene understanding for autonomous driving. It can encapsulate data from heterogeneous sensor sources like radars, LiDARs, cameras and ultrasonics. At the core of occupancy grid (OG) generation, there is usually an inverse sensor model (ISM), which infers the occupancy representation from the sensor readings. Traditional ISMs are characterized by a very rigid structure, suited only for one sensor type, and specific occupancy grid representation. This paper proposes a novel ISM framework, which offers a separation between free and occupied space, supporting both Bayesian and Dempster-Shafer OG representations. The framework is especially useful when dealing with multiple different sensors where custom or preselected probability distribution can be applied. The presented ISM architecture is modular and flexible, which is described in an illustrative example of application customized for different detection sources. © 2020, Springer Nature Switzerland AG.

关键词： Probability distributions

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