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Multibody simulation for tracking error reduction in solar tracking robots

AIP Conference Proceedings 2023年第1期2872卷

作者： Aldo Hernández-Díaz Diego A. Flores-Hernández Alberto Luviano-Juárez Sergio Isai Palomino-Resendiz Itzamá López-Yáñez National Polytechnic Institute - UPIITA Applied Dynamic Systems Laboratoy Mexico City 07340 Mexico National Polytechnic Institute - UPIITA Advanced Robotics Laboratory Mexico City 07340 Mexico National Polytechnic Institute - ESIME-ZAC Department of Control and Automation Mexico City 07738 Mexico National Polytechnic Institute - CIDETEC Mexico City 07738 Mexico

Currently, the use of renewable energy sources such as solar energy, collected by photovoltaic technology, has gained ground in the energy sector. Its use has been popularised due to the fact that it is considered a clean energy, that is a type of energy is produced without burning fossil fuels which are a cause of global warming, among other environmental damages. In order to optimize the energy harvesting through photovoltaic technology, it is necessary to maintain a perpendicular incidence of the sun rays with the photovoltaic module, leading to the use of solar tracking systems that demand the application of trajectory tracking control strategies that minimize the tracking errors while ensuring the lowest energy consumption of the robotic system. In this work, a comprehensive multibody simulation was carried out to obtain a concrete appreciation of the behavior of the tracking system prior to an experimental implementation. This type of simulations allows us to simulate complete systems formed by solid links and rigid joints that were previously designed, and with a calculated analytical model (Kinematic and Dynamic). Furthermore, the obtained simulator allows us to apply a variety of control strategies that are represented by means of 3D simulations which are very similar to the actual experimental results, so that it would be possible to estimate the ªtracking error results° without the necessity of a physical implementation. From the kinematic and dynamic models of a solar tracker of two degrees of freedom, released in an azimuthal-elevation configuration, a PID controller and a passivity-based controller were implemented in Matlab-Simscape®, obtaining simulations of a solar trajectory tracking minimizing the error between the reference and the solar tracker.

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Preliminary study in motion assistance of soft exoskeleton robot based on data-driven kinematics model learning

Preliminary study in motion assistance of soft exoskeleton r...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Li, Ning Li, Jialin Yang, Tie Yang, Yang Yu, Peng Liu, Lianqing Qin, Wanglin Xi, Ning Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing University of Chinese Academy of Sciences Beijing100049 China Shenyang Jianzhu University Institutes for Robotics and Intelligent Manufacturing Shenyang110000 China Emerging Technologies Institute Department of Industrial and Manufacturing Systems Engineering University of Hong Kong Pokfulam Hong Kong

ISBN: (纸本)9781728163215

Exoskeleton is widely used to enhance human mobility. Especially in recent years, the soft exoskeleton robots have developed rapidly, which could realize natural human-machine physiological coupling. However, the motion patterns and physiological parameters are significant various between different subjects. The parameters of the soft exoskeletons change differently during motion. In this paper, we proposed kinematics model based on data-driven model learning. The proposed model learning method not only has the fast learning ability of model-based controller, but also has the adaptability of sensor-based controller. Firstly, we use the data of the rigid model to pre-train the kinematics model network, which can make the output of the network consistent with the kinematics model. Then, we use the sensors to collect the actual motion data and send the motion data into the pre-trained neural network model. By increasing the iteration times of training, the network model outputs model parameters that are consistent with the trend of the simulation model. Through the training and learning of the bionic motion platform, the speed of learning adaptation in human body can be accelerated. © 2019 IEEE.

关键词： Physiological models

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Atomic force microscopy studies on cellular elastic and viscoelastic properties

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Science China(Life Sciences) 2018年第1期61卷 57-67页

作者： Mi Li Lianqing Liu Ning Xi Yuechao Wang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Department of Industrial and Manufacturing Systems Engineering The University of Hong Kong Hong Kong China

In this work, a method based on atomic force microscopy (AFM) approach-reside-retract experiments was established to simultaneously quantify the elastic and viscoelastic properties of single cells. First, the elastic and viscoelastic properties of normal breast cells and cancerous breast cells were measured, showing significant differences in Young’s modulus and relaxation times between normal and cancerous breast cells. Remarkable differences in cellular topography between normal and cancerous breast cells were also revealed by AFM imaging. Next, the elastic and viscoelasitc properties of three other types of cell lines and primary normal B lymphocytes were measured; results demonstrated the potential of cellular viscoelastic properties in complementing cellular Young’s modulus for discerning different states of cells. This research provides a novel way to quantify the mechanical properties of cells by AFM, which allows investigation of the biomechanical behaviors of single cells from multiple aspects.

关键词： atomic force microscopy cell mechanical properties viscoelastic properties Young＇s modulus relaxation time

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Pareto Continual Learning: Preference-Conditioned Learning and Adaption for Dynamic Stability-Plasticity Trade-off

arXiv

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arXiv 2025年

作者： Lai, Song Zhao, Zhe Zhu, Fei Lin, Xi Zhang, Qingfu Meng, Gaofeng Department of Computer Science City University of Hong Kong Hong Kong Centre for Artificial Intelligence and Robotics HK Institute of Science & Innovation Chinese Academy of Sciences China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China City University of Hong Kong Shenzhen Research Institute Hong Kong University of Science and Technology of China China

Continual learning aims to learn multiple tasks sequentially. A key challenge in continual learning is balancing between two objectives: retaining knowledge from old tasks (stability) and adapting to new tasks (plasticity). Experience replay methods, which store and replay past data alongside new data, have become a widely adopted approach to mitigate catastrophic forgetting. However, these methods neglect the dynamic nature of the stability-plasticity trade-off and aim to find a fixed and unchanging balance, resulting in suboptimal adaptation during training and inference. In this paper, we propose Pareto Continual Learning (ParetoCL), a novel framework that reformulates the stability-plasticity trade-off in continual learning as a multi-objective optimization (MOO) problem. ParetoCL introduces a preference-conditioned model to efficiently learn a set of Pareto optimal solutions representing different trade-offs and enables dynamic adaptation during inference. From a generalization perspective, ParetoCL can be seen as an objective augmentation approach that learns from different objective combinations of stability and plasticity. Extensive experiments across multiple datasets and settings demonstrate that ParetoCL outperforms state-of-the-art methods and adapts to diverse continual learning scenarios. Copyright © 2025, The Authors. All rights reserved.

关键词： Multi-task learning

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Industrial robot rotate vector reducer fault detection based on hidden markov models

Industrial robot rotate vector reducer fault detection based...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Zhang, Yinlong An, Haibo Ding, Xiaojian Liang, Wei Yuan, Mingze Ji, Chunyang Tan, Jindong Shenyang Institute of Automation Guangzhou Chinese Academy of Sciences Guangzhou511548 China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Fifth Electronic Instituteof MIIT Guangzhou510610 China Department of Mechanical Aerospace and Biomedical Engineering University of Tennessee KonxvilleTN37996 United States

ISBN: (纸本)9781728163215

Reliable fault detection of rotate vector (RV) reducer is of paramount importance for the long-term maintenance of high-precision industrial robots. This paper proposes a Hidden Markov Model (HMM) based RV reducer fault detection using Acoustic Emission (AE) measurements. Compared with the conventional faults from the common rotating machinery (such as bearings and gears), the fault from the RV reducer is more complicated and undetectable due to its inherent inline and two-stage meshing structure. To this end, this work modifies the HMM model by taking into account not only the current observations and previous states, but also the subsequent series of observations within the posteriori probability framework. Through this way, the random and unknown disturbance, which is common in the industrial scenarios, could be reduced. Besides, the HMM is also applied to separate the AE signal bulks within one cycle that has 39 subcycles, which is a critical step for AE signal pre-processings. The proposed method has been evaluated on our collected AE signal dataset from the RV reducer in the industrial robotic platform. The experimental results and analysis validate that the proposed HMM based RV Reducer fault detection model can reliably and accurately detect reducer faults. © 2019 IEEE.

关键词： Hidden Markov models

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Spherical interpolated convolutional network with distance-feature density for 3D semantic segmentation of point clouds

arXiv

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arXiv 2020年

作者： Wang, Guangming Yang, Yehui Zhang, Huixin Liu, Zhe Wang, Hesheng Department of Automation Insititue of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China Department of Computer Science and Technology University of Cambridge United Kingdom

The semantic segmentation of point clouds is an important part of the environment perception for robots. However, it is difficult to directly adopt the traditional 3D convolution kernel to extract features from raw 3D point clouds because of the unstructured property of point clouds. In this paper, a spherical interpolated convolution operator is proposed to replace the traditional grid-shaped 3D convolution operator. This newly proposed feature extraction operator improves the accuracy of the network and reduces the parameters of the network. In addition, this paper analyzes the defect of point cloud interpolation methods based on the distance as the interpolation weight and proposes the self-learned distance-feature density by combining the distance and the feature correlation. The proposed method makes the feature extraction of spherical interpolated convolution network more rational and effective. The effectiveness of the proposed network is demonstrated on the 3D semantic segmentation task of point clouds. Experiments show that the proposed method achieves good performance on the ScanNet dataset and Paris-Lille-3D dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Accelerating surgical robotics research: A review of 10 years with the da Vinci research kit

arXiv

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arXiv 2021年

作者： D’Ettorre, Claudia Mariani, Andrea Stilli, Agostino Rodriguez y Baena, Ferdinando Valdastri, Pietro Deguet, Anton Kazanzides, Peter Taylor, Russell H. Fischer, Gregory S. DiMaio, Simon P. Menciassi, Arianna Stoyanov, Danail University College London LondonW1W 7EJ United Kingdom Pisa Italy Mechanical Engineering Department Imperial College London United Kingdom STORM Lab Institute of Robotics Autonomous Systems and Sensing School of Electronic and Electrical Engineering University of Leeds Leeds United Kingdom Johns Hopkins University Baltimore United States Automation and Interventional Medicine Laboratory Worcester Polytechnic Institute WorcesterMA United States Intuitive Surgical Inc SunnyvaleCA United States

Robotic-assisted surgery is now well-established in clinical practice and has become the gold standard clinical treatment option for several clinical indications. The field of robotic-assisted surgery is expected to grow substantially in the next decade with a range of new robotic devices emerging to address unmet clinical needs across different specialties. A vibrant surgical robotics research community is pivotal for conceptualizing such new systems as well as for developing and training the engineers and scientists to translate them into practice. The da Vinci Research Kit (dVRK), an academic and industry collaborative effort to re-purpose decommissioned da Vinci surgical systems (Intuitive Surgical Inc, CA, USA) as a research platform for surgical robotics research, has been a key initiative for addressing a barrier to entry for new research groups in surgical robotics. In this paper, we present an extensive review of the publications that have been facilitated by the dVRK over the past decade. We classify research efforts into different categories and outline some of the major challenges and needs for the robotics community to maintain this initiative and build upon it. © 2021, CC BY.

关键词： Robotic surgery

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Stairs reconstruction with 3D point cloud for gait generation of lower limb exoskeleton robot

Stairs reconstruction with 3D point cloud for gait generatio...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Feng, Yachun Xia, Linqing He, Yong Wang, Can Yan, Zefeng Wu, Xinyu Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781728163215

With the aging of the population, a considerable number of elderly persons suffer from walking disability. Lower limb exoskeleton robots have been proved to be effective in rehabilitation training and walking assistance. Though significant advancement has been made in the last decade, lacking the ability of adapting to complex terrain is one of the main challenges that restrict the wide application of exoskeleton robots. Thus we focus on the environmental perception and corresponding gait pattern generation of lower limb assistant exoskeleton. In this paper, we introduce a method to generate gait of exoskeleton walking on a stair, which applies the L-0 minimization-based acquisition and reconstruction of stairs information through 3D Point Cloud. The results of experiments show that our method can precisely measure the physical dimension information of stairs. © 2019 IEEE.

关键词： Stairs

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Classification and applications of titanium and its alloys: A review

Journal of Alloys and Compounds Communications

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Journal of Alloys and Compounds Communications 2024年 3卷

作者： Mojtaba Najafizadeh Sahar Yazdi Mansoor Bozorg Mehran. Ghasempour-Mouziraji Morteza Hosseinzadeh Masoumeh Zarrabian Pasqual Cavaliere School of Materials Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China Faculty of Chemical and Materials Engineering Shahrood University of Technology Shahrood *** Iran Department of Innovation Engineering University of Salento Via per Arnesano Lecce 73100 Italy School of Medical Sciences Shahrood Branch Islamic Azad University Shahrood Iran TEMA - Centre for Mechanical Technology and Automation University of Aveiro Portugal LASI Intelligent Systems Associate Laboratory Guimarães Portugal Engineering and Sustainable Technology ManagementIndustry 4.0: Automation Robotics & 3D Manufacturing SRH Hochschule Berlin Germany Department of Engineering Ayatollah Amoli Branch Islamic Azad University Amol Iran

Due to its numerous properties, iron is one of the most useful materials on the planet. The mechanical and physical properties of iron and its alloys are suitable and manageable. These alloys have significant issues like heavyweight, low corrosion resistivity and some other limitations. The researchers and companies for solving problems look out for other alternative materials. Titanium and its alloys, according to the researchers, have a huge variety of engineering applications. Titanium and titanium alloys have high strength and corrosion resistance, and they perform well at high temperatures up to nearly 600 °C. Titanium and its alloys have a density of about 60 % that of steel and its alloys, and about 50 % that of nickel alloys. Even though titanium and its alloys have cost and supply problems, they're utilized in numerous industries, which includes aerospace, automotive, and navy projects. Titanium and its alloys have unique properties, indicating that they are cost-effective components that require special manufacturing techniques. This study aims to explore the potential of titanium and its alloys to replace iron in various engineering applications. Addressing the critical need for materials with superior performance characteristics is essential for advancing technological development.

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A generalized model for predicting the optimal overlap rate and height of successive single-layer involved in laser metal deposition process based on the aspect ratio

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Optics & Laser Technology 2025年 191卷

作者： Enjie Dong Tingyu Chang Gan Li Ze Liu Liming Xia Linjie Zhao Junwen Lu Jiaxuan Chen Mingjun Chen Jian Cheng State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Heilongjiang 150001 China Department of Mechanical Engineering City University of Hong Kong Hong Kong China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Guangdong 518055 China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou 310027 China Aircraft Repair & Overhaul Plant/Sichuan Province Engineering Technology Research Center of General Aircraft Maintenance Civil Aviation Flight University of China Guanghan 618307 China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou 450000 China

The surface flatness of single-layer islands deposition is essential for high-quality multi-layer component deposition and the stability of the Laser metal deposition (LMD) manufacturing process. The aspect ratio of single-track deposition and the overlap rate are critical factors influencing the flatness of single-layer island deposition. Existing methods for determining the optimal overlap rate, whether through experimental approaches or simplified recursive overlap models, still suffer from long development cycles and limited accuracy. In this study, a generalized, efficient and reliable model for predicting the optimal overlap rate only using the aspect ratio of the single-track deposition as the input parameter was developed after fully understanding the influence of the aspect ratio and overlap rate on the morphology, stacking effect and flatness of single-layer islands. Besides, a prediction model for the height of the single-layer island, based on the input parameters of the aspect ratio and the overlap rate has also been developed. Further, verification datasets from different experimental batches and materials were used to validate the accuracy and generalizability of the island height prediction model. The validation results indicated that the relative error between the predicted and actual values was less than 10%. The single-track aspect ratio can be directly used to guide the LMD multi-layer component deposition, regardless of the combination of powder and substrate materials, using these reliable and generalized prediction models for the optimal overlap rate and the island height developed in current study. The single-layer island deposition stage was completely eliminated, thereby significantly shorten the development cycle and reduce the cost of LMD process parameter development.

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