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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Ali Tourani Hriday Bavle Jose Luis Sanchez-Lopez Rafael Muñoz Salinas Holger Voos Automation and Robotics Research Group Interdisciplinary Centre for Security Reliability and Trust (SnT) University of Luxembourg Luxembourg Department of Computer Science and Numerical Analysis Rabanales Campus University of Cordoba Spain Faculty of Science Technology and Medicine University of Luxembourg Luxembourg

Fiducial markers can encode rich information about the environment and aid Visual SLAM (VSLAM) approaches in reconstructing maps with practical semantic information. Current marker-based VSLAM approaches mainly utilize markers for improving feature detections in low-feature environments and/or incorporating loop closure constraints, generating only low-level geometric maps of the environment prone to inaccuracies in complex environments. To bridge this gap, this paper presents a VSLAM approach utilizing a monocular camera along with fiducial markers to generate hierarchical representations of the environment while improving the camera pose estimate. The proposed approach detects semantic entities from the surroundings, including walls, corridors, and rooms encoded within markers, and appropriately adds topological constraints among them. Experimental results on a real-world dataset collected with a robot demonstrate that the proposed approach outperforms a marker-based VSLAM baseline in terms of accuracy, given the addition of new constraints while creating enhanced map representations. Furthermore, it shows satisfactory results when comparing the reconstructed map quality to the one rebuilt using a LiDAR SLAM approach.

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Machine Learning Algorithms for Natural Language Processing Tasks: A Case of COVID-19 Twitter data (Thailand)

Machine Learning Algorithms for Natural Language Processing ...

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International Conference on Computational science and Computational Intelligence (CSCI)

作者： Kunyanuth Kularbphettong Rujijan Vichivanives Pannawat Kanjanaprakarn Jaruwan Chutrtong Nareenart Ruksuntorn Computer Science Program Suan Sunandha Rajabhat University Bangkok Thailand Faculty of Science and Technology Suan Sunandha Rajabhat University Bangkok Thailand Robotics Engineering program Faculty of Industrial Technology Suan Sunandha Rajabhat University Bangkok Thailand

This paper presents the use of natural language processing for the problem of information extraction and sentiment analysis. The dataset is from Twitter that has the information of people mentioning about COVID-19, this study has two tasks: (i) classification approach for information extraction task and (ii) deep learning approach for sentiment analysis task. In information extraction task, the data was gathered from twitter that related to COVID-19 information, and the sequence labelling method applied to classify text before giving it to classification algorithms (K-NN, Naïve Bayes, Decision Tree, Random Forest, and SVM). In sentiment analysis task, data was classified by convert the word into index and using word embedding, then to process deep learning algorithm (Bi-directional GRU). The accuracy of two tasks are 98% and 79% respectively.

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ROBUST: 221 Bugs in the Robot Operating System

arXiv

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arXiv 2024年

作者： Timperley, Christopher S. van der Hoorn, Gijs Santos, André Deshpande, Harshavardhan Wąsowski, Andrzej School of Computer Science Carnegie Mellon University United States Department of Cognitive Robotics faculty of Mechanical Maritime and Materials Engineering Delft University of Technology Netherlands VORTEX CoLab Portugal Fraunhofer Institute for Manufacturing Engineering and Automation IPA Germany Department of Computer Science IT University of Copenhagen Denmark

As robotic systems such as autonomous cars and delivery drones assume greater roles and responsibilities within society, the likelihood and impact of catastrophic software failure within those systems is increased. To aid researchers in the development of new methods to measure and assure the safety and quality of robotics software, we systematically curated a dataset of 221 bugs across 7 popular and diverse software systems implemented via the Robot Operating System (ROS). We produce historically accurate recreations of each of the 221 defective software versions in the form of Docker images, and use a grounded theory approach to examine and categorize their corresponding faults, failures, and fixes. Finally, we reflect on the implications of our findings and outline future research directions for the community. © 2024, CC BY-NC-SA.

关键词： Robot Operating System

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One-Piece 3D-Printed Legs Using Compliant Mechanisms That Produce Effective Propulsive Force for Hexapod Robot Locomotion

One-Piece 3D-Printed Legs Using Compliant Mechanisms That Pr...

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IEEE International Conference on Soft robotics (RoboSoft)

作者： Atsushi Kaneko Dai Owaki Masahiro Shimizu Takuya Umedachi Faculty of Textile Science and Technology Shinshu University Ueda Nagano Japan Department of Robotics Graduate School of Engineering Tohoku University Sendai Japan Department of Systems Innovation Graduate School of Engineering Science Osaka University Toyonaka Osaka Japan

Bio-inspired soft robotic legs can be designed by utilizing continuous deformation to perform desired functions such as increasing propulsion force. Previous studies of legged robots have improved locomotion performance by simplifying animal legs as a single spring and mimicking the function of its elasticity during locomotion. This study proposes a one-piece 3D-printed leg that can kick the ground backward strongly by increasing the horizontal component of the elastic force (i.e., by designing two-dimensional elasticity). The geometry and stiffness of the leg were optimized via a combination of physical simulation and a genetic algorithm to achieve the function. Experiments using a prototype hexapod robot were conducted to compare a leg designed using the proposed method and two additional deteriorated types of legs by measuring locomotion speed. Angle of attack (angle at which the legs touch the ground) was also changed in this experiment. The experimental results indicate that designing the two-dimensional elasticity of legs can contribute to increasing propulsion force, resulting in higher locomotion speed. This study suggests that soft robotic parts with various functions, such as hands and arms, can be designed using continuous deformation and one-piece 3D-printed parts.

关键词： Legged locomotion Manufacturing processes Deformation Force Prototypes Soft robotics Elasticity

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Rlsnake: A hybrid reinforcement learning approach for road detection 24

Rlsnake: A hybrid reinforcement learning approach for road d...

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2021 24th ISPRS Congress Commission III: Imaging Today, Foreseeing Tomorrow

作者： Botteghi, N. Sirmacek, B. Ünsalan, C. Robotics and Mechatronics Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Netherlands Smart Cities School of Creative Technology Saxion University of Applied Sciences Netherlands Electrical and Electronics Engineering Faculty of Engineering Marmara University Turkey

Road network detection from very high resolution satellite and aerial images is highly important for diverse domains. Although an expert can label road pixels in a given image, this operation is prone to error and quite time consuming remembering that road maps must be updated regularly. Therefore, various computer vision based automated algorithms have been proposed in the last two decades. Nevertheless, due to the diversity of scenes, the field is still open for robust methods which might detect roads on different resolution images of different type of environments. In this study, we picked an earlier proposed road detection method which works based on traditional computer vision and probability theory algorithms. We improved it by further steps using reinforcement learning theory. With the help of the novel hybrid technique (traditional computer vision method combined with reinforcement learning based artificial intelligence), we achieved a solution that we call RLSnake. This new method can learn new image scenes and resolutions rapidly and can work reliably. We believe that the proposed RLSnake will be a significant step in the remote sensing field in order to develop solutions which might increase performance by combining the power of traditional and new techniques. © 2021 International Archives of the Photogrammetry, Remote Sensing and Spatial Information sciences - ISPRS Archives. All rights reserved.

关键词： Reinforcement learning

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Position control of humanoid thorax based on fuzzy PID controller

Position control of humanoid thorax based on fuzzy PID contr...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Siyuan Fang Zaojun Fang Chengbin Peng Chi Zhang Guiling Yang Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo Institute of Materials & Technology Engineering Chinese & Academy of Sciences Ningbo China Ningbo Institute of Materials & Technology Engineering Chinese & Academy of Sciences Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo China College of Science & Technology Ningbo University Ningbo China

Respiration is the most notable vital sign of humans so that it is usually employed to diagnose disease in medicine. Recently, a solution is proposed to decrease the cost of healthcare using flexible stretchable sensors to monitor respiration. However, the sensor is difficult to test millions of cycles on a real human body, which is essential to ensure accuracy and repeatability in practical applications. In this paper, a new humanoid thoracic cavity that mimics rib expansion/constriction is exhibited. Then, a position control based on Fuzzy PID method is presented. Focused on the scenario, the performance between the common PID method and the Fuzzy PID method is investigated. Firstly, the position control based on the Fuzzy PID method is constructed by utilizing position output error and its rate. Then, three gain parameters of PID are adjusted online according to the established fuzzy rules. Finally, the above two methods are compared by simulation and experiments. In a simulation, the fuzzy PID control algorithm improves the response speed, shortens the adjustment time, and meets the requirements of the system for high response and high accuracy. Besides, an experiment is carried out on a humanoid chest prototype. the results show that the control period of the presented method is shortened by about 50% v.s. the traditional PID under the step signal input. Tracking marked points using a laser tracker, the maximum tracking error is 0.0523 mm, the minimum error is 0.0450 mm, and the average error is 0.0473mm. Therefore, the presented method is validated to improve the performance of the humanoid chest.

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Matching Design and Multi-objective Optimization of Integarated joint for collaborative robot

Matching Design and Multi-objective Optimization of Integara...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Hui Zhang Chi Zhang Feng Yi Qinghao Du Pingping Lv Shupei Li Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Ningbo China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo China Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo China

ISBN: (数字)9798350360868

ISBN: (纸本)9798350360875

Driving joints are the core components of collaborative robots, but existing joints have low torque density and poor dynamic response performance. This article proposes a novel integrated joint composed of a hollow AFPM motor and an embedded planetary gear reducer, which enhance the output performance, i.e., high torque density and efficiency, high dynamic response. Aiming at achieving the superior performance, a matching-oriented design method is proposed for the integrated joint. This design method reveals the impacts mechanisms between the structural parameters (including AFPM motor and planetary reducer) and the output performance. The multi-objective optimization is conducted to obtain the optimal design parameters by using NSGA-II. The optimized design is compared with the initial one, which indicates that the weight of the optimized joint is reduced by 49g, the joint torque density is increased by 36.8%, and the dynamic response performance is improved by 31.5%.

关键词： Industrial electronics Torque Gears Design methodology Collaborative robots Motors Structural engineering

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An Innovative Smart Irrigation Using Embedded and Regression-Based Machine Learning Technologies for Improving Water Security and Sustainability

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IEEE Access 2025年 13卷 100731-100751页

作者： Abdennabi Morchid Abdennacer Elbasri Zahra Oughannou Hassan Qjidaa Rachid El Alami Badre Bossoufi Saleh Mobayen Paweł Skruch LIMAS Laboratory Faculty of Sciences Dhar El Mahraz Sidi Mohamed Ben Abdellah (SMBA) University Fes Morocco Department of Data Science Mundiapolis University of Casablanca Campus Nouaceur Casablanca Morocco Innovation in Mathematics and Intelligent Systems (IMIS) Laboratory Ibn Zohr University Agadir Morocco Systems and Sustainable Environment Laboratory (SED) Faculty of Engineering Sciences (FSI) Private University of Fez (UPF) Fes Morocco Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Douliu Taiwan Energy Systems Research Center Khazar University Baku Azerbaijan Department of Automatic Control and Robotics AGH University of Science and Technology Kraków Poland

Global agriculture is facing major challenges such as food security, sustainable water management, and the preservation of natural resources. Water scarcity, exacerbated by climate change, requires adopting more efficient agricultural practices. Traditional irrigation systems, often imprecise, contribute to water wastage. The use of embedded systems and machine learning offers a solution for optimizing irrigation according to local conditions and actual crop needs while contributing to food security and environmental sustainability. This study proposes an innovative approach to irrigation management, integrating real-time data and predictive models to improve irrigation efficiency. This study proposes an irrigation system based on embedded systems, using sensors and algorithms to collect and analyze data in order to optimize water management. The system adjusts irrigation levels according to specific crop needs, thus contributing to more sustainable water management. Using ML algorithms like linear regression algorithms to model the relationships between environmental factors and crop water requirements, enabling accurate prediction of required irrigation levels based on data collected by sensors. The use of embedded systems such as the ESP32, combined with temperature, humidity, and water level sensors, has enabled the development of an autonomous and efficient system for collecting data in real-time and processing it for decision-making. The proposed model has an MAE of 0.8434, an RMSE of 0.8434, and a coefficient (R2 Score) of 0.4044, offering soil moisture prediction accuracy. Furthermore, the training time of our model is 0.00253 seconds, while the prediction time is 0.00117 seconds. These results show not only the performance of the proposed model in terms of accuracy but also its computational efficiency, outperforming some of the studies mentioned. The results of the study show a significant reduction in water consumption, with a marked improvement in water

关键词： Climate change Embedded systems Smart agriculture Irrigation Food security Optimization methods Machine learning Machine learning algorithms Sustainable development Water resources Water monitoring Environmental management

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Research on hybrid flow-shop scheduling based on improved genetic algorithm

Research on hybrid flow-shop scheduling based on improved ge...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Haopeng Chen Zaojun Fang Caiming Zhong Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo Institute of Materials & Technology Engineering Chinese & Academy of Sciences Ningbo China Ningbo Institute of Materials & Technology Engineering Chinese & Academy of Sciences Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo China College of Science & Technology Ningbo University Ningbo China

Aiming at the scheduling problem in the production process of hybrid flow-shop, a hybrid flow-shop scheduling model with the objective of minimizing the makespan is established, and a neighborhood search adaptive genetic algorithm (NSAGA) based on heuristic decoding strategy is proposed. An encoding strategy based on the first stage processing sequence and a decoding strategy based on a heuristic rule are used to guide the algorithm to find the optimal solution quickly. In order to speed up the convergence of the algorithm, the elitism strategy is introduced into the genetic operation, and adaptive crossover and mutation strategy based on sigmoid function is designed. In order to enhance the local search capability of the algorithm, a neighborhood search strategy is designed. Finally, the effectiveness and superiority of NSAGA for solving the hybrid flow-shop scheduling problem (HFSP) with different scales are verified by simulation experiments.

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Measurements of loads acting on an electric bus in urban traffic

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Procedia Structural Integrity 2023年 47卷 723-731页

作者： Bartłomiej Walczak Piotr Malaca Dariusz Michalak Wiesław J. Staszewski AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics 30 Mickiewicza Avenue 30-059 Krakow Poland Solaris Bus & Coach sp. z o.o. Obornicka 46 Bolechowo-Osiedle 62-005 Owińska Poland

The design of city buses is a process in which a great role is given to optimizing the weight of the structure. In order to achieve this goal responsibly, all strength requirements must be taken into account, especially those related to fatigue. In the bus industry, there are no commonly available guidelines and standards for design and manufacturers must rely on their best knowledge. Proper selection of loads acting on the structure during normal operation is an essential step. The article presents the process of load measurements on a bus in urban traffic using the example of a three-axle electric bus. Firstly, based on of the finite element simulation, key measurement locations on the bus were selected. They included both the superstructure and elements of the vehicle's suspension system. Stresses on the vehicle's supporting structure, accelerations on both sprung and unsprung masses, and forces in the suspension system were measured. The measurements in the first stage were focused on typical maneuvers such as sudden braking, turns, and speed bumps. The second part was focused on urban traffic. Together with the local transportation company, routes with a different spectrum of quality have been selected, and the test drives have been done. After this stage, the registered signals were analyzed. As a result, guidelines for fatigue calculations were developed, and road sections of key importance for fatigue strength were selected. Finally, they were scanned and will be used for dynamic fatigue analysis in the future.

关键词： Electric bus fatigue analysis load measurements bus durability

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