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arXiv 2019年

作者： Li, Lening Fu, Jie Robotics Engineering Program Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

In this paper, we develop a model-free approximate dynamic programming method for stochastic systems modeled as Markov decision processes to maximize the probability of satisfying high-level system specifications expressed in a subclass of temporal logic formulas—syntactically co-safe linear temporal logic. Our proposed method includes two steps: First, we decompose the planning problem into a sequence of sub-problems based on the topological property of the task automaton which is translated from a temporal logic formula. Second, we extend a model-free approximate dynamic programming method to solve value functions, one for each state in the task automaton, in an order reverse to the causal dependency. Particularly, we show that the run-time of the proposed algorithm does not grow exponentially with the size of specifications. The correctness and efficiency of the algorithm are demonstrated using a robotic motion planning example. Copyright © 2019, The Authors. All rights reserved.

关键词： Specifications

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Miniature magnetic robots for in-pipe locomotion 21

Miniature magnetic robots for in-pipe locomotion

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robotics Transforming the Future - 21st International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines, CLAWAR 2018

作者： Mills, George H. Liu, Jason H.W. Kaddouh, Bilal Y. Jackson, Andrew E. Richardson, Robert C. Department of Mechanical Engineering University of Leeds LeedsLS2 9JT United Kingdom Institute of Design Robotics and Optimisation LeedsLS2 9JT United Kingdom

ISBN: (纸本)9781916449008

Inspection of both small and large diameter bore pipelines for pipe integrity and defect identification with a single system has previously been impractical;especially using wall-press locomotion methods with low adaptive range. A miniature magnetic wall-climbing robot has been developed as a robotic solution for the inspection of 50mm bore diameter pipelines which can scale in-pipe geometry obstacles to access larger connected pipelines. Using magnetic arrays directed through steel flux plates within the wheels, the robot uses magnetic forces to adhere to the pipe. The system is 3D printed and includes soft printed material rubber wheels. The robot prototype is wirelessly driven, controlled remotely through serial Bluetooth communication radio at 2.4 GHz rated up to 100m. The robot's unique compact geometry and magnetic design allows it to scale concave right-angle wall cases in just a 50mm diameter bore. By entering pipe networks through these small existing access points the robot removes the need for expensive drilling procedures required to fit launch vessels. © CLAWAR Association.

关键词： Pipelines

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engineering stacking-induced topological phase transitions in bilayer heterostructures

arXiv

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arXiv 2025年

作者： Bordoloi, Arjyama Kaplan, Daniel Singh, Sobhit Department of Mechanical Engineering University of Rochester RochesterNY14627 United States Center for Materials Theory Department of Physics and Astronomy Rutgers University PiscatawayNJ08854-8019 United States Materials Science Program University of Rochester RochesterNY14627 United States Center for Coherence and Quantum Optics University of Rochester RochesterNY14627 United States

Nonmagnetic topological insulators (TIs) are known for their robust metallic surface/edge states that are protected by time-reversal symmetry, making them promising candidates for next-generation spintronic and nanoelectronic devices. Traditional approaches to realizing TIs have focused on inducing band inversion via strong spin-orbit coupling (SOC), yet many materials with substantial SOC often remain topologically trivial. In this work, we present a materials-design strategy for engineering topologically non-trivial phases, e.g., quantum spin Hall phases, by vertically stacking topologically trivial Rashba monolayers in an inverted fashion. Using BiSb as a prototype system, we demonstrate that while the BiSb monolayer is topologically trivial (despite having significant SOC), an inverted BiSb-SbBi bilayer configuration realizes a non-trivial topological phase with enhanced spin Hall conductivity. We further reveal a delicate interplay between the SOC strength and the interlayer electron tunneling that governs the emergence of a nontrivial topological phase in the bilayer heterostructure. This phase can be systematically tuned using an external electric field, providing an experimentally accessible means of controlling the system’s topology. Our magnetotransport studies further validate this interplay, by revealing g-factor suppression and the emergence a zeroth Landau level. Notably, the inverted bilayer heterostructure exhibits a robust and tunable spin Hall effect, with performance comparable to that of state-of-the-art materials. Thus, our findings unveil an alternative pathway for designing and engineering functional properties in 2D topological systems using topologically trivial constituent monolayers. Copyright © 2025, The Authors. All rights reserved.

关键词： Bismuth alloys

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Research on Novel Concept of Hybrid Electric Vehicle Using Removable Engine-Generator

Research on Novel Concept of Hybrid Electric Vehicle Using R...

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Huy Huu Nguyen Jongmyung Kim Giyeon Hwang Sangyul Lee Minjae Kim Department of Mechanical Engineering Myongji University Yong-in South Korea Department of Robotics and Automation Engineering Hoseo University Dangjin South Korea

Hybrid electric vehicles (HEVs) have been widely used due to their significant impacts in urban driving areas. However, the charge of additional weight of the engine/generator is a huge burden. This paper studies a modern concept to reduce unnecessary weight using the removable engine- generator set that can be can assembled and disassembled by hands. It can be used according to the requirements of the driver such that additional constructions of charging stations are no longer needed. Moreover, charging with driving is feasible unlike Electric Vehicles (EVs). A novel hybrid electric vehicle is tested by city driving cycles and a remarkable improvement in the fuel efficiency in comparison to the conventional hybrid electric vehicle, especially plug-in hybrid vehicle could be demonstrated.

关键词： Hybrid electric vehicles Charging stations Urban areas Radio frequency

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An experimental study on bond strength of abaca fiber as natural FRP material

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IOP Conference Series: Materials Science and engineering 2021年第1期1087卷

作者： T Saidi Z Amalia M Hasan I Hasanuddin W Salvana Akram Department of Civil Engineering Universitas Syiah Kuala Banda Aceh Indonesia Department of Mechanical Engineering Universitas Syiah Kuala Banda Aceh Indonesia Civil Engineering Postgraduate Program Department of Civil Engineering Universitas Syiah Kuala Banda Aceh Indonesia Engineering Doctoral Program Faculty of Engineering Universitas Syiah Kuala Banda Aceh Indonesia

The use of fiber reinforced polymer (FRP) has been implemented as an alternative for strengthening and repairing methods. Nowadays, the use of natural material for FRP has been developed in order to minimize the disadvantage effects to nature due to synthetic FRP material and economic reason. In this paper, an experimental study was carried out to evaluate the bond strength of abaca fiber as natural reinforced polymer (NFRP) material in reinforced concrete (RC) beams. The test specimen was a beam that had cross-section area of 100 × 100mm2 and 300mm length. Single rebar was used in this study with 10mm diameter of rebar. Artificial crack was applied in order to consider the initial crack by using cardboard between the concrete. Two externally bonded strengthened beams with a different type of abaca fiber arrangement, bond length, and thickness were applied on the concrete surface. The test was conducted by applying a tension load on the beam until the specimen reach its failure. The results showed that the bond strength decrease as the bond length becomes longer because the maximum load was almost constant for different bond length. The maximum load was approximately around 4 tf for short and long bond length. The compatibility of abaca fiber and rebar was also monitored. Both abaca fiber and rebar able to stand the load compactly. Abaca fiber composite laminate had a similar trend with rebar at the same location where an artificial crack was made. Furthermore, the arrangement and thickness of the abaca fiber composite laminate affected the results.

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Simulation of vision-based tactile sensors using physics based rendering

arXiv

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arXiv 2020年

作者： Agarwal, Arpit Man, Timothy Yuan, Wenzhen The Robotics Institute Carnegie Mellon University 5000 Forbes Ave PittsburghPA15213 United States The Department of Mechanical Engineering Carnegie Mellon University 5000 Forbes Ave PittsburghPA15213 United States

Tactile sensing has seen a rapid adoption with the advent of vision-based tactile sensors. Vision-based tactile sensors provide high resolution, compact and inexpensive data to perform precise in-hand manipulation and human-robot interaction. However, the simulation of tactile sensors is still a challenge. In this paper, we built the first fully general optical tactile simulation system for a GelSight sensor using physics based rendering techniques. We propose physically accurate light models and show in-depth analysis of individual components of our simulation pipeline. Our system outperforms previous simulation techniques qualitatively and quantitative on image similarity metrics. Our code and experimental data is open-sourced at project page. © 2020, CC BY-NC-SA.

关键词： Tactile sensors

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Multi-step ahead Bitcoin Price Forecasting Based on VMD and Ensemble Learning Methods

Multi-step ahead Bitcoin Price Forecasting Based on VMD and ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Ramon Gomes da Silva Matheus Henrique Dal Molin Ribeiro Naylene Fraccanabbia Viviana Cocco Mariani Leandro dos Santos Coelho Industrial & Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) Curitiba Parana Brazil Department of Mathematics Federal Technological University of Parana (UTFPR) Pato Branco Parana Brazil Mechanical Engineering Graduate Program (PPGEM) Pontifical Catholic University of Parana (PUCPR) Curitiba Parana Brazil Department of Electrical Engineering Federal University of Parana (UFPR) Curitiba Parana Brazil

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Bitcoin is the leading currency in the cryptocurrency market capturing attention worldwide. Forecasting the Bitcoin price as accurate as possible is essential, but due to its high volatility this task is challenging. Many researchers try, through the years, to develop efficient models for predicting the Bitcoin price using several different data-driven approaches. The objective of this paper is to develop a novel decomposition-ensemble learning model that combines Variational Mode Decomposition (VMD) and Stacking-ensemble learning (STACK) with machine learning algorithms to forecast the Bitcoin price multi-step ahead. The algorithms are k-Nearest Neighbors, Support Vector Regression with Linear kernel, Feed-forward Artificial Neural Network with single-layer perceptron, Generalized Linear Model, and Cubist. Correlation matrix (CORR), principal component analysis (PCA), and Box-Cox transformation (BOXCOX) were used as data preprocessing techniques. Estimating the performance of the proposed models (namely VMD-STACK-CORR, VMD-STACK-PCA, and VMD-STACK-BOXCOX) using relative root mean square error, symmetric mean absolute percentage error, and absolute percentage error measures, defined that for one-day-ahead forecast VMD-STAK-BOXCOX model presented the better performance, and for two and three-days-ahead forecast VMD-STACK-CORR model was chosen, compared to VMD, STACK, and machine learning algorithms models' performance. Diebold-Mariano statistical test was conducted to evaluate a reduction in forecasting errors. Therefore, the proposed models (VMD-STACK-CORR, VMD-STACK-PCA, and VMD-STACK-BOXCOX) indeed forecast accurately Bitcoin price and outperformed the compared models (VMD, STACK, and machine learning models).

关键词： Predictive models Biological system modeling Data models Bitcoin Training Machine learning algorithms

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A Deep Learning-based Framework for Environment-adaptive Navigation of Size-adaptable Microswarms

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engineering 2024年

作者： Jialin Jiang Lidong Yang Shihao Yang Li Zhang Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong 999077 China Shenzhen Research Institute The Chinese University of Hong Kong Shenzhen 518000 China Department of Industrial and Systems Engineering The Hong Kong Polytechnic University (PolyU) Hong Kong 999077 China Department of Surgery The Chinese University of Hong Kong Hong Kong 999077 China CUHK T Stone Robotics Institute The Chinese University of Hong Kong Hong Kong 999077 China Chow Yuk Ho Technology Center for Innovative Medicine The Chinese University of Hong Kong Hong Kong 999077 China Multi-Scale Medical Robotics Center Hong Kong Science Park Hong Kong 999077 China

Actively controllable microswarms have been a rapidly developing research field with appealing characteristics. Autonomous collision-free navigation of microswarms in confined environments is suitable for various applications, including targeted therapy and delivery. However, several challenges remain unaddressed. First, microswarms possess varying dimensions, and a path planning method suitable to swarms with different dimensions is essential to avoid obstacles. Second, studies on the environment-adaptive navigation of reconfigurable microswarms are limited. Therefore, the planning of the pattern distribution of microswarms based on the local working environment should be examined. This study proposes a deep learning (DL)-based environment-adaptive navigation scheme for swarms. The controller provides reference moving directions for swarms of different sizes in static and dynamic scenarios. Moreover, a pattern-distribution planner was designed to navigate transformable swarms in unstructured environments. To validate the proposed scheme, we applied Fe 3 O 4 nanoparticles swarms as a case study. The proposed scheme enables motion and pattern planning for microrobots of multiple sizes and reconfigurability in various working environments, which could foster a general navigation system for reconfigurable microswarms of different sizes.

关键词： Microswarms Automatic navigation Deep learning (DL)

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Effect of ultrasonic vibration on pineapple drying

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AIP Conference Proceedings 2022年第1期2681卷

作者： Patipat Thanompongchart Pakamon Pintana Tanapong Tangoon Nakorn Tippayawong 1Energy Management Engineering Program Faculty of Industrial Technology Uttaradit Rajabhat University Uttaradit Thailand 2School of Renewable Energy Maejo University Chiang Mai Thailand 3Department of Mechanical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand

Thailand is known to have various types of tropical fruits. Fruits are generally produced in large quantities annually. Preservation can add value and extend the shelf life of these fruit products. One of the most popular methods of preservation is the drying process. A solar-powered dryer is widely used in fruit drying because of its low cost in terms of energy use. Ultrasonic vibration technology can be used to induce water movement in a product resulting in a faster dehydration rate. This can shorten the overall drying time and preserve the vitamins and nutrients in the product. In this work, the application of ultrasonic vibration to fruit drying was investigated. The raw material tested was pineapple. Drying was carried out in a hot air oven set to a temperature of 60 °C, with an applied vibration frequency of 40 kHz continuously for a short duration of 1 min. Three periods of the applied ultrasonic cycle (on for every 10, 20, 30 min) were tested for an overall drying time of 10 h. The results showed that for a cycle of every 10 min with vibration turned on, the initial moisture content of pineapples was reduced from 86.9 to 47.9 % wet basis at a maximum drying rate of 48.6 g/h, compared to 40.5 g/h from normal drying without applied vibration. The reduced drying time led to reduced energy consumption. This technique has the potential to be applied to other types of fruits and dryers.

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The EEG-based lower limb exoskeleton system optimization strategy based on channel selection

The EEG-based lower limb exoskeleton system optimization str...

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2019 IEEE International Conference on Real-Time Computing and robotics, RCAR 2019

作者： Long, Xingguo Ma, Yue Ma, Xunju Yan, Zefeng Wang, Can Wu, Xinyu Shenzhen 518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology CAS University of Chinese Academy of Sciences Chinese University of Hong Kong Department of Mechanical and Automation Engineering

ISBN: (纸本)9781728137261

Compared with traditional exoskeleton robots, the brain-computer interface (BCI) based lower limb exoskeleton system can directly control the robot by recording the user's brain activity signals, such as the electroencephalogram (EEG). The brain activity signals contain the original and global motion intention, which is capable of operating the walking assistance exoskeleton device in a way that matches the operator's will more closely. In our previous work, an EEG-based lower limb exoskeleton system and a human-machine interaction paradigm that orient to the scenario of dynamic motion is designed. However, the EEG sensor configuration is a time-consuming process and limit the utility of the EEG based system. Besides, channel redundancy makes it difficult to explore experimental mechanisms of the designed paradigm. Therefore, in this paper, a heuristic channel selection optimization algorithm with the L1 norm is applied to the BCI system. Based on the data of four subjects, we verify the performance of the selected optimal channel subset and explore a universal optimal channel subset. Tested on another two new subjects, the universal optimal subset shows a promising prospect in improving the performance of the EEG-based exoskeleton system. © 2019 IEEE.

关键词： Electroencephalography

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