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Chinese Control Conference (CCC)

作者： Mingyuan Wu Shuting Wang Jie Meng Yuanlong Xie School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan China

For visual Simultaneous Localization and Mapping (VSLAM), the camera positional estimation is deeply affected by environmental factors such as the surrounding feature situation and light condition. In this case, the accuracy and robustness of the positional estimation in visual odometry can be improved by the assistance of artificial landmarks. Based on this, a correction method based on AprilTag is proposed for ORB-SLAM3 to optimize the pose estimation of landmark VSLAM. Firstly, a point cloud map is built with Tag mapping embedded through the high accuracy 6 DOF positional transformation data provided by AprilTag. With this, the tracking module of ORB-SLAM3 is improved the positioning accuracy during pose estimating. In this way, the computational resources for estimating the camera pose can be reduced while guaranteeing the accuracy of pose estimation. Through subsequent validation experiments, the effectiveness of AprilTag-aided solution for ORB-SLAM3 is demonstrated for pose estimation optimization of landmark VSLAM.

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Low-cost, accurate robotic harvesting system for existing mushroom farms

Low-cost, accurate robotic harvesting system for existing mu...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Panagiotis Mavridis Nikolaos Mavrikis Athanasios Mastrogeorgiou Panagiotis Chatzakos TWI-Hellas Halandri GR Control Systems Lab School of Mechanical Engineering NTUA GR AI Innovation Centre University of Essex Colchester UK

This paper presents a robotic mushroom harvesting solution, consisting of an actuated scanning vision system integrated into a gantry robot. The system is capable of performing segmentation and pose estimation of the mushrooms on Dutch shelves commonly used in growing farms worldwide. The vision system employs an active stereo RGB-D camera able to capture a 360° scene of the mushroom bed, providing a high quality reconstruction of the mushroom caps. The YOLOv5 algorithm is used for the detection and size classification of the mushrooms, while a two-step model-fitting method is developed for the pose estimation task. The actuated carriage is compact, designed for operation in real mushroom-growing farms and intended to be used together with a soft gripper. The robot has five actuated degrees of freedom (DoFs), three for the linear motion on the shelves, and two DoFs for achieving the desired orientation for the gripper. In a real harvesting scenario, the robot sequentially scans the selected areas and accurately places the gripper in the appropriate angle of attack utilising our pose estimation method together with our visual servoing module for minor adjustments. The results were promising on all trials using 3D printed white button mushrooms on real soil.

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Study of the Applicability of Flat Reflectors in Photovoltaic Plants under Conditions of the Russian Far North

Study of the Applicability of Flat Reflectors in Photovoltai...

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International Russian Automation Conference (RusAutoCon)

作者： Nikolay Mestnikov Ahmad Alzakkar Yuri Samofalov Institute of Physical and Technical Problems of North SB RAS North-Eastern Federal University Yakutsk Russia Faculty of Mechanical and Electrical Engineering Albaath University Homs Syria Institute of Electric Power Systems and Network Kazan State Power Engineering University Kazan Russia

ISBN: (数字)9798350349818

ISBN: (纸本)9798350349825

The paper is devoted to the study of an applied method for increasing the energy efficiency of solar energy facilities. The purpose of the article is to study the applicability of flat reflectors in photovoltaic plants operated in the northern regions of Russia. In this work the following tasks were solved: development of an algorithm for performing field studies, conducting field studies using flat reflectors for photovoltaic panels, determination of the performance indicators of a photovoltaic plant before and after using flat reflectors and performing a technical and economic assessment of the application of the proposed technical measure. A thin metal film made of aluminum alloy with impurities of silicon, tin, copper and iron in the range [0.5 – 1] % is used as a flat reflector. As a result of the work performed, it was established that in the case of using flat reflectors, the average daily output of a photovoltaic plant increases from 20 % to 37.4 %. These reflectors increase the surface temperature of photovoltaic panels 23.4 %, which reduces power generation 1.2 %. In this regard, layers of heat-insulating materials such as polyethylene terephthalate polymer film and metallized polyethylene terephthalate are added to the back of the flat reflector. It has been recorded that these layers reduce the share of reflection of the energy of thermal radiation from the sun to the photovoltaic panel with a subsequent decrease in its surface temperature 10 %.

关键词： Photovoltaic systems Economics Polyethylene Impurities Tin Aluminum alloys Silicon Iron Energy efficiency Copper

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Collaborative learning model predictive control for repetitive tasks

arXiv

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arXiv 2022年

作者： Chanfreut, Paula Maestre, José María Camacho, Eduardo F. Borrelli, Francesco The Department of Systems and Automation Engineering University of Seville Spain The Department of Mechanical Engineering University of California at Berkeley BerkeleyCA94701 United States

This paper presents a cloud-based learning model predictive controller that integrates three interacting components: a set of agents, which must learn to perform a finite set of tasks with the minimum possible local cost;a coordinator, which assigns the tasks to the agents;and the cloud, which stores data to facilitate the agents’ learning. The tasks consist in traveling repeatedly between a set of target states while satisfying input and state constraints. In turn, the state constraints may change in time for each of the possible tasks. To deal with it, different modes of operation, which establish different restrictions, are defined. The agents’ inputs are found by solving local model predictive control (MPC) problems where the terminal set and cost are defined from previous trajectories. The data collected by each agent is uploaded to the cloud and made accessible to all their peers. Likewise, similarity between tasks is exploited to accelerate the learning process. The applicability of the proposed approach is illustrated by simulation results. Copyright © 2022, The Authors. All rights reserved.

关键词： Model predictive control

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Dense Network-Based Spectral-Polarization Image Fusion: Multispectral Data Enhancement via Encoder-Decoder Approach 6

Dense Network-Based Spectral-Polarization Image Fusion: Mult...

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6th International Conference on Information Technologies and Electrical engineering, ICITEE 2023

作者： Karim, Shahid Tong, Geng Li, Jinyang Yu, Yiting Ibrar, Muhammad Mehmood, Faisal Research & Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen518057 China College of Mechanical Engineering Northwestern Polytechnical University Xi'an710072 China Key Laboratory of Micro/Nano Systems for Aerospace Ministry of Education Northwestern Polytechnical University Xi'an710072 China Shaanxi Province Key Laboratory of Micro and Nano Electro-Mechanical Systems Northwestern Polytechnical University Xi'an701172 China Research Center of Smart Sensing Chips Ningbo Institute of Northwestern Polytechnical University Ningbo315103 China Software College Shenyang Normal University Shenyang China School of Electronic and Computer Engineering Shenzhen Graduate School Peking University Shenzhen518055 China

ISBN: (纸本)9798400708299

Images are obtained by perceiving the sunlight reflected by objects or scenes, and due to limited solar irradiance, spatial resolution certainly decreases. In contrast, multispectral sensors hold the spatial information of ground objects even though the obtained images only have a few bands, which means that the obtained images have high spatial but insufficient spectral resolution. To overcome these limitations, we have developed a spectral and polarization image fusion technique that improves several perspectives of image fusion, such as intensity, edges, textures, and substantial information. Our proposed method utilizes an encoder-decoder approach, which contains dense and convolutional blocks to simulate the source images. The polarization images have been used to develop DoLP images that help to improve fused images' quality. We can perceive the visual quality of fused images from the experimental results. © 2023 ACM.

关键词： Image fusion

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Parametric Continuous-Time Blind System Identification

Parametric Continuous-Time Blind System Identification

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IEEE Conference on Decision and Control

作者： Augustus Elton Rodrigo A. González James S. Welsh Cristian R. Rojas Minyue Fu College of Engineering Science and Environment University of Newcastle Callaghan NSW Australia Department of Mechanical Engineering Eindhoven University of Technology Eindhoven The Netherlands Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden

In this paper, the blind system identification problem for continuous-time systems is considered. A direct continuous-time estimator is proposed by utilising a state-variable-filter least squares approach. In the proposed method, coupled terms between the numerator polynomial of the system and input parameters appear in the parameter vector which are subsequently separated using a rank-1 approximation. An algorithm is then provided for the direct identification of a single-input single-output linear time-invariant continuous-time system which is shown to satisfy the property of correctness under some mild conditions. Monte Carlo simulations demonstrate the performance of the algorithm and verify that a model and input signal can be estimated to a proportion of their true values.

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FLAMELET MODELING OF THERMO-DIFFUSIVELY UNSTABLE HYDROGEN-AIR FLAMES

arXiv

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arXiv 2023年

作者： Böttler, Hannes Lulic, Haris Steinhausen, Matthias Wen, Xu Hasse, Christian Scholtissek, Arne Technical University of Darmstadt Department of Mechanical Engineering Simulation of reactive Thermo-Fluid Systems Otto-Berndt-Straße 2 Darmstadt64287 Germany

In order to reduce CO2 emissions, hydrogen combustion has become increasingly relevant for technical applications. In this context, lean H2-air flames show promising features but, among other characteristics, they tend to exhibit thermo-diffusive instabilities. The formation of cellular structures associated with these instabilities leads to an increased flame surface area which further promotes the flame propagation speed, an important reference quantity for design, control, and safe operation of technical combustors. While many studies have addressed the physical phenomena of intrinsic flame instabilities in the past, there is also a demand to predict such flame characteristics with reduced-order models to allow computationally efficient simulations. In this work, a H2-air spherical expanding flame, which exhibits thermo-diffusive instabilities, is studied with flamelet-based modeling approaches both in a-priori and a-posteriori manner. A recently proposed Flamelet/Progress Variable (FPV) model, with a manifold based on unstretched planar flames, and a novel FPV approach, which takes into account a large curvature variation in the tabulated manifold, are compared to detailed chemistry (DC) calculations. Both flamelet approaches account for differential diffusion utilizing a coupling strategy which is based on the transport of major species instead of transporting the manifold control variables. First, both FPV approaches are assessed in terms of an a-priori test with the DC reference dataset. Thereafter, the a-posteriori assessment contains two parts: a linear stability analysis of perturbed planar flames and the simulation of the spherical expanding flame. Both FPV models are systematically analyzed considering global and local flame properties in comparison to the DC reference data. It is shown that the new FPV model, incorporating large curvature variations in the manifold, leads to improved predictions for the microstructure of the corrugated flame front and t

关键词： Hydrogen

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Interactive Explainable Deep Survival Analysis

Interactive Explainable Deep Survival Analysis

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Lu Wang Xinyu Qin Jingyan Jiang Yan Li Winston Liaw Dept. of Biomedical Engineering University of Houston Houston TX USA Dept. of Health Systems and Population Health Sciences University of Houston Houston TX USA Dept. of Mechanical and Industrial Engineering Argonne National Laboratory University of Toronto Toronto Canada

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Being able to accurately predict the time to event of interest, commonly known as survival analysis, is extremely beneficial in healthcare for modeling disease progression, identifying prognostic factors, assessing risk of health by building survival models in health aging, precision medicine, supporting clinical decision making. In order to be usable by healthcare providers, survival analysis models need to be accurate, interpretable, and trustable. Efficient interaction between human stakeholders (e.g., developers, domain experts and/or end-users) and clear model interpretation not only improve the model performance but also enhance human trust. The primary goal of this paper is to develop algorithm and method that support implementation of trustworthy and time-efficient data-driven decision making for prevention and early intervention. Our experimental results on one public cancer datasets demonstrate the algorithm efficiency for predicting survival time of cancer patients.

关键词： Analytical models Explainable AI Prevention and mitigation Precision medicine Decision making Medical services Predictive models Prediction algorithms Stakeholders Cancer

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Developing the Performance and Longevity of Electric Vehicle Batteries Through the Implementation of Thermal Management systems

Developing the Performance and Longevity of Electric Vehicle...

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Disruptive Technologies (ICDT), International Conference on

作者： N. Venkatesh Kumar Praveen Kumar. C B. Anandan B. A. Devan G. Sasikala V.R. Kavitha Department of Chemistry VSB Engineering College Karur Tamil Nadu India Department of Electronics and Instrumentation Engineering SRM Valliammai Engineering College Chengalpet Tamil Nadu India Department of Mechanical Engineering Siddharth Institute of Engineering & Technology Puttur Andhrapradesh India Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Computer Science and Business Systems R.M.K. Engineering College Kavarapettai Tamil Nadu India

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

Electric vehicles, also known as EVs, are quickly becoming more popular as a more environmentally friendly alternative to conventional automobiles powered by internal combustion engines. The performance and longevity of electric vehicle batteries, on the other hand, are crucial aspects that can have a substantial impact on the adoption of these batteries and their overall efficiency. As a result of the fact that temperature fluctuations have a significant impact on the degradation of batteries, thermal management systems are absolutely necessary in order to keep batteries functioning at their best and to extend their lifespan. The development and implementation of better thermal management systems for electric vehicle batteries is the primary emphasis of this field of research. In the first step of this process, we will examine the current status of electric vehicle battery technology as well as the difficulties connected with thermal control. After that, we investigate a variety of thermal management solutions, such as air cooling, liquid cooling, and phase change materials, in order to determine which methods are the most efficient for a variety of battery chemistries and operating situations. The design and simulation of a unique thermal management system that blends liquid cooling with superior heat dissipation materials is an important part of our study. This system is designed to manage thermal energy. In order to analyze the heat transfer that occurs within the battery pack and to optimize the design parameters of the thermal management system, we make use of computational fluid dynamics (CFD) and finite element analysis (FEA). We analyze the effectiveness of the suggested thermal management system by conducting a number of experiments and simulations. Our results show that the system is effective in terms of temperature regulation, energy efficiency, and the impact it has on the life of the battery. According to the facts that we have gathered, the deploymen

关键词： Phase change materials Degradation Liquid cooling Computational fluid dynamics Thermal management Electric vehicles Regulation Batteries Thermal analysis Thermal degradation

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Learning Quiet Walking for a Small Home Robot

arXiv

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arXiv 2025年

作者： Watanabe, Ryo Miki, Takahiro Shi, Fan Kadokawa, Yuki Bjelonic, Filip Kawaharazuka, Kento Cramariuc, Andrei Hutter, Marco Robotic Systems Lab Department of Mechanical Engineering ETH Zurich Switzerland Sony Group Corporation Japan National University of Singapore Singapore Nara Institute of Science and Technology Japan University of Tokyo Japan

As home robotics gains traction, robots are increasingly integrated into households, offering companionship and assistance. Quadruped robots, particularly those resembling dogs, have emerged as popular alternatives for traditional pets. However, user feedback highlights concerns about the noise these robots generate during walking at home, particularly the loud footstep sound. To address this issue, we propose a sim-to-real based reinforcement learning (RL) approach to minimize the foot contact velocity highly related to the footstep sound. Our framework incorporates three key elements: learning varying PD gains to actively dampen and stiffen each joint, utilizing foot contact sensors, and employing curriculum learning to gradually enforce penalties on foot contact velocity. Experiments demonstrate that our learned policy achieves superior quietness compared to a RL baseline and the carefully handcrafted Sony commercial controllers. Furthermore, the trade-off between robustness and quietness is shown. This research contributes to developing quieter and more user-friendly robotic companions in home environments. Copyright © 2025, The Authors. All rights reserved.

关键词： Multipurpose robots

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