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2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Ferdous, Dilruba Saha, Suman Ray, Ranjit CSIR-Central Mechanical Engineering Research Institute Electric Mobility and Tribology Research Group Durgapur India Ghaziabad201002 India CSIR-Central Mechanical Engineering Research Institute Underwater Robotics & Autonomous Systems Group Durgapur India

ISBN: (纸本)9798350378092

Autonomous underwater vehicle (AUV) has a significant influence on marine applications due to its endurance and effectiveness in performing challenging missions. Since most AUVs employ batteries as prime energy storage, their underwater mission time is limited. Moreover, they need to be hauled out of the water for recharging batteries prior to every mission, which is a time consuming and tedious process. Hence, recharging AUV batteries underwater using a wireless power transfer technology is a feasible and secure option to overcome the aforementioned limitation. In this paper, a resonance based inductive power transfer system for wireless charging of AUVs has been developed. Further, the performance of wireless charging system is validated through simulation in MATLAB/Simulink platform and verified through preliminary experimentation carried out in a 1 kW laboratory scale hardware prototype. The experimental results in saline water environment showcase a power transfer efficiency of 85-86% considering a gap of 3 cm between primary and secondary coils. © 2024 IEEE.

关键词： Wireless charging

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Diffusion-based learning of contact plans for agile locomotion 23

Diffusion-based learning of contact plans for agile locomoti...

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23rd IEEE-RAS International Conference on Humanoid Robots, Humanoids 2024

作者： Dhédin, Victor Ravi, Adithya Kumar Chinnakkonda Jordana, Armand Zhu, Huaijiang Meduri, Avadesh Righetti, Ludovic Schölkopf, Bernhard Khadiv, Majid Munich Institute of Robotics and Machine Intelligence Technical University of Munich Germany New York University Tandon School of Engineering United States Max-Planck Institute for Intelligent Systems Tübingen Germany

ISBN: (纸本)9798350373578

Legged robots have become capable of performing highly dynamic maneuvers in the past few years. However, agile locomotion in highly constrained environments such as stepping stones is still a challenge. In this paper, we propose a combination of model-based control, search, and learning to design efficient control policies for agile locomotion on stepping stones. In our framework, we use nonlinear model predictive control (NMPC) to generate whole-body motions for a given contact plan. To efficiently search for an optimal contact plan, we propose to use Monte Carlo tree search (MCTS). While the combination of MCTS and NMPC can quickly find a feasible plan for a given environment (a few seconds), it is not yet suitable to be used as a reactive policy. Hence, we generate a dataset for optimal goal-conditioned policy for a given scene and learn it through supervised learning. In particular, we leverage the power of diffusion models in handling multi-modality in the dataset. We test our proposed framework on a scenario where our quadruped robot Solo12 successfully jumps to different goals in a highly constrained environment (video). © 2024 IEEE.

关键词： Multipurpose robots

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Au-MPN@Ag Nanocomposite-Assisted Mass Spectrometry for Metabolite Detection

Au-MPN@Ag Nanocomposite-Assisted Mass Spectrometry for Metab...

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2024 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale, 3M-NANO 2024

作者： Sang, Qi Li, Yanyan Liu, Wanshan Wang, Yuning Qian, Kun Shanghai Jiao Tong University State Key Labtoratory of Systems Medicine for Cancer School of Biomedical Engineering Institute of Medical Robotics and Shanghai Academy of Experiment Medicine Shanghai China

ISBN: (纸本)9798350362107

Sensitive detection of metabolites in biofluids plays an important role in disease diagnosis. Herein, we synthesized a novel noble metal based nanocomposite using metal-polyphenol network (MPN) as coordination and redox reaction. The formed Au-MPN@Ag nanocomposite exhibited excellent metabolite detection performance in laser desorption ionization mass spectrometry (LDI-MS). Notably, Au-MPN@Ag nanocomposite based LDI-MS platform achieved direct detection of metabolites in biofluids without any sample pretreatment. Our work provides a new advanced platform for metabolic analysis towards in vitro diagnostics. © 2024 IEEE.

关键词： Redox reactions

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Data Entry Errors Detection for Industrial Quality Control Variables Using Data-Driven Models 16th

Data Entry Errors Detection for Industrial Quality Control ...

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16th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2024

作者： Salles, Rodrigo Leiria, Joana Mendes, Jérôme Institute of Systems and Robotics ARISE University of Coimbra Coimbra Portugal CEMMPRE ARISE Department of Mechanical Engineering University of Coimbra Coimbra Portugal

ISBN: (纸本)9783031817236

In modern industrial environments, quality control is imperative for ensuring product reliability and operational efficiency. Despite advancements in automatic data collection and data-driven models for quality processes, certain critical variables still require manual entry due to the branch of activity from which they originate, leading to potential errors from human involvement. This paper focuses on developing and applying two methodologies, Soft Sensors (SS) and Principal Component Analysis (PCA), to detect data entry errors in quality control variables. The developed methodologies were tested across three industrial datasets and the following error types were studied: blank spaces, duplicates, measurement errors, order errors, and extra number errors. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Model predictive control

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SoSpider:A bio-inspired multimodal untethered soft hexapod robot for planetary lava tube exploration

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Science China(Technological Sciences) 2023年第11期66卷 3090-3106页

作者： NIU LiZhou DING Liang ZHANG ShengJie YANG HuaiGuang GAO HaiBo DENG ZongQuan LIU GuangJun HOSSAIN Mokarram State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150001China Department of Aerospace Engineering Ryerson UniversityToronto ON M5B 2K3Canada Zienkiewicz Institute for Modelling Data and AISwansea UniversitySwansea SA18ENUnited Kingdom

Soft robots have tremendous potential for applications in various fields,owing to their safety and flexibility embedded at the material *** robots,especially bio-inspired soft legged robots,have become one of the most active fields of current research in robotics thanks to their superior mobility and ability to face complex ***,it is arduous to establish a dynamic simulation model for soft robots,owing to their hyper-redundant degrees of freedom,hyper-elasticity,and nonlinearity of their soft *** this study,we designed,simulated,and fabricated a hexapod robot that achieves walking,crawling,pronking,and rolling with wheeled legs plus a soft body capable of shape change.A robot prototype was fabricated using 3D printing technology and soft silicone pneumatic ***,battery power,and control boards were integrated into the body of the robot for untethered *** have explored the capabilities of the robot in different conditions,especially in scenarios that simulate lunar and Martian environments,demonstrating the motion performance of the *** results have shown promising potentials of the developed robot for future applications in planetary lava tube *** experimental and simulation results also show good agreements that indicate the potential predictive roles of simulation tools for soft robot design,planning,and control.

关键词： multimodal soft robot pneumatic simulation planetary exploration

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Design of Gravity Compensation Scheme for Passive Lifting Method of Multi-degree Freedom Robotic Arm 18

Design of Gravity Compensation Scheme for Passive Lifting Me...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Sun, Jing Wei, Chaoran Chen, Haotai Wang, Bin Li, Xingguang Zhang, Qiang Beijing Institute of Control Engineering Space Drive and Manipulation Mechanism Laboratory Beijing China State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China

ISBN: (纸本)9798350312201

Before launching a spacecraft, it is necessary to undergo micro low gravity simulations on the ground to test its reliability. The lifting method is not limited by movement time and space, and can simulate long-term low gravity environments. However, the degree of freedom of spatial mechanisms is gradually increasing, and the motion is becoming increasingly complex, making traditional lifting methods unable to meet the needs. In response to the above issues, a lifting gravity simulation scheme for a multi degree of freedom robotic arm that can achieve complex motion is proposed. The design adopts a single sling combined with a hanger to avoid interference during the motion process. Finally, simulation and experiments have proven the feasibility of the scheme - it can achieve efficient unloading without affecting the normal movement of the equipment. © 2023 IEEE.

关键词： Robotic arms

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Learning Rat-Like Behavior for a Small-Scale Biomimetic Robot

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engineering 2022年第10期17卷 232-243页

作者： Zihang Gao Guanglu Jia Hongzhao Xie Qiang Huang Toshio Fukuda Qing Shi Key Laboratory of Biomimetic Robots and Systems(Beijing Institute of Technology) Ministry of EducationBeijing 100081China Intelligent Robotics Institute School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China

Existing biomimetic robots can perform some basic rat-like movement primitives(MPs)and simple behavior with stiff combinations of these *** mimic typical rat behavior with high similarity,we propose parameterizing the behavior using a probabilistic model and movement ***,an analysis of fifteen 10 min video sequences revealed that an actual rat has six typical behaviors in the open field,and each kind of behavior contains different bio-inspired combinations of eight *** used the softmax classifier to obtain the behavior-movement hierarchical probability ***,we specified the MPs using movement parameters that are static and *** obtained the predominant values of the static and dynamic movement parameters using hierarchical clustering and fuzzy C-means clustering,*** predominant parameters were used for fitting the rat spinal joint trajectory using a second-order Fourier series,and the joint trajectory was generalized using a back propagation neural network with two hidden ***,the hierarchical probability model and the generalized joint trajectory were mapped to the robot as control policy and commands,*** implemented the six typical behaviors on the robot,and the results show high similarity when compared with the behaviors of actual rats.

关键词： Biomimetic Bio-inspired robot Neural network learning system Behavior generation

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Fault Detection in Electric Drives Based on LSTM Autoencoder Model Machine Learning Approach 25

Fault Detection in Electric Drives Based on LSTM Autoencoder...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Demidova, Galina Privalov, Daniil Semenov, Denis Lukichev, Dmitry Liu, Zhitao Anuchin, Alecksey Faculty of Control System and Robotics ITMO University Saint-Petersburg Russia Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Department of Electric Drives Moscow Power Engineering Institute Moscow Russia

ISBN: (纸本)9798350389234

Fault detection in electric drives is crucial for ensuring operational reliability and minimizing downtime. This paper provides a brief overview of the methods based on machine learning used for fault detection in electric drives. Additional this research presents a machine learning approach that utilizes the Long Short-Term Memory Autoencoder model for fault detection deal with bearing faults. A flowchart illustrating the implementation steps of the Long Short-Term Memory Autoencoder algorithm is included. Additionally, a case study on bearing faults in an electric drive system is presented to demonstrate the advantage of the proposed approach. By training the Long Short-Term Memory Autoencoder on operational data, accurate prediction of bearing faults is achieved, enabling timely maintenance interventions. It is shown that in the 7th epoch of training, the model achieved a notably high accuracy more than 99%. The results highlight the potential of Long Short-Term Memory Autoencoder models as a valuable tool for fault detection in electric drives, thereby improving system reliability and performance. © 2024 IEEE.

关键词： Machine learning

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Optimization of Cylindrical Blades for Wind Turbine Based on Magnus Effect

Optimization of Cylindrical Blades for Wind Turbine Based on...

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2023 International Conference on Electromechanical and Energy systems, SIELMEN 2023

作者： Lukin, Aleksandr Demidova, Galina Lukichev, Dmitry Poliakov, Nikolai Anuchin, Alecksey ITMO University Faculty of Control Systems and Robotics Saint-Petersburg Russia Moscow Power Engineering Institute Electric Drives Department Moscow Russia

ISBN: (纸本)9798350315240

Wind turbines based on the Magnus effect open new prospects in terms of energy generation for areas with low average wind speeds. The main feature of these turbines is rotating cylinders which are used to create lift instead of blades. Due to this unconventional design, different parameters of the cylinder, such as mass and moment of inertia, can greatly affect the dynamic characteristics of such energy systems. The goal of this paper was to present an approach to structural optimization of a cylinder flange of the experimental Magnus effect-based wind turbine. The proposed approach, presented as an algorithm, allows us to determine input data for the preferred structural optimization software and achieve lightweight, low-inertia parts. Control simulation has shown that optimized parts ensure a high enough factor of safety while also significantly reducing the moment of inertia. © 2023 IEEE.

关键词： Finite element method

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Energy-Consumption Optimization Control for Lunar Rover's Travel with Torque-Distribution-strategy in Rear Wheels

Energy-Consumption Optimization Control for Lunar Rover's Tr...

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2024 IEEE International Conference on Control Science and systems engineering, ICCSSE 2024

作者： Li, Delun Cao, Jianfei Chen, Yiliang Xie, Zongwu Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China Beijing Institute of Spacecraft System Engineering Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing China

ISBN: (纸本)9798331517199

In anticipation of future extensive lunar surface operations, lunar rovers are required to advance towards higher speeds and improved energy conservation. When traveling at high speeds on the lunar surface, the vehicle's energy expenditure is greatly amplified by the influence of the terrain, particularly in conditions where driving and steering are coupled. This paper proposes an energy-saving control strategy for lunar rovers that employs dynamic rear-axle torque distribution, with the goal of optimizing transient energy consumption during travel. To tackle the challenge of non-differentiable functions within the optimization objectives, we suggest using a zeroth-order gradient optimization method for resolution, dynamically constraining the range of control parameters to fulfill the dynamic torque distribution objectives as needed for the task. The energy-saving control effectiveness of the algorithm has been confirmed through simulation, demonstrating a minimum energy-saving ratio of at least 4%, which increases to over 11% as the speed level rises, offering a valuable technical solution for the energy optimization of lunar rovers. © 2024 IEEE.

关键词： Rovers

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