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IEEE-RAS International Conference on Humanoid Robots

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

ISBN: (数字)9798350373578

ISBN: (纸本)9798350373585

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).

关键词： Legged locomotion Monte Carlo methods Supervised learning Humanoid robots Diffusion models Quadrupedal robots Predictive control

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Hybrid Path-lifting Algorithm and Equivalence of Stability Results for MRP-based Control Strategies

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IEEE Transactions on Automatic Control 2025年

作者： Martins, Luis Cardeira, Carlos Oliveira, Paulo Universidade de Lisboa Institute of Mechanical Engineering Instituto Superior Técnico Lisboa Portugal Universidade de Lisboa Institute of Mechanical Engineering Institute for Systems and Robotics Instituto Superior Técnico Lisboa Portugal

This paper proposes an innovative hybrid dynamic mechanism to uniquely and robustly lift a path from the three-dimensional special orthogonal group to the modified Rodrigues parameters (MRP) space. The path-lifting mechanism leverages the unique properties of the MRP representation and is crucial for developing a novel framework for the equivalence of stability results between these topological spaces. The new hybrid methodology allows the design and analysis of an attitude feedback controller in the topologically less complex MRP space with the guarantee that its asymptotic and exponential stability properties directly translate to the attitude dynamics in the base space. Furthermore, the resulting interconnection is impervious to the unwinding phenomenon. The design and evaluation of an MRP-based controller demonstrate the application, practical relevance, and advantages of the proposed algorithm alongside the novel results for equivalence of stability between spaces. The solution renders the attitude space dynamics robustly globally asymptotically stable and robustly semi-globally exponentially stable, illustrating the potential of this novel approach. © 1963-2012 IEEE.

关键词： Asymptotic Stability Attitude Control Exponential Stability Hybrid systems Modified Rodrigues parameters Unwinding

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Digital Twin Development for a Quality Control Cell

Digital Twin Development for a Quality Control Cell

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Marcella Cavalcanti Hugo Costelha Carlos Neves André Martins Luís Perdigoto School of Technology and Engineering Polytechnic of Leiria Leiria Portugal Institute for Systems Engineering and Computers - Coimbra (INESCC) Leiria Portugal Technological University of the Shannon: Midlands Midwest Limerick Ireland Institute of Systems and Robotics (ISR) Coimbra Portugal

The Digital Twin is one of the enabling technologies of Industry 4.0, Cyber-Physical systems and Smart Factories. In this context, Digital Twins can be developed for being employed through the entire lifecycle of a system, for design, operation, monitoring, maintenance, and even fault prediction and reconfiguration. This paper describes the development of a Digital Twin for a Quality Control cell that is part of a larger manufacturing process in the automotive industry. The virtual environment was built using ABB RobotStudio, the communication between devices in the cell was implemented with OPC UA (UA. NET and open62541), and the process data are registered in a database using MySQL. The results show a fully functional simulation of the cell's behaviour and future development will include the connection of the Digital Twin with the real system.

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Implementation and Validation of the CautiousBug Algorithm in ROS Noetic

Implementation and Validation of the CautiousBug Algorithm i...

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Information, Control, and Communication Technologies (ICCT), International Conference on

作者： Roman Mishenin Alexander Eryomin Tatyana Tsoy Evgeni Magid Department of Computer Engineering (DCE) Moscow Institute of Electronics and Mathematics Higher School of Economics Moscow Russian Federation Laboratory of Intelligent Robotics Systems (LIRS) Institute of Information Technology and Intelligent Systems Kazan Federal University Kazan Russian Federation

ISBN: (数字)9798331517564

ISBN: (纸本)9798331517571

In this paper, we present an implementation of the CautiousBug algorithm within the Noetic distribution of the Robot Operating System (ROS). Bug algorithms address a challenge of robot navigation in unknown environments without relying on pre-existing maps or constructing new ones. These algorithms utilize odometry data, operate without a map, require minimal computational resources, and can be implemented on relatively simple hardware. A C++ software application was created to simulate a behavior of the CautiousBug algorithm in various environments within the Gazebo simulator. This application allows for an analysis of key metrics, including accumulated yaw, distance traversed and algorithm's runtime. We conducted a set of virtual experiments in the Gazebo to evaluate the CautiousBug performance.

关键词： Runtime Navigation Software architecture Working environment noise Operating systems Software algorithms Software Robustness Path planning Robots

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A Vision-Based Two-Stage Fruit Outer Diameter Detection Method

A Vision-Based Two-Stage Fruit Outer Diameter Detection Meth...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Hao, Yifei Yan, Shuaizheng Wu, Zhengxing He, Bingwei Li, Chenghua Yu, Junzhi Fuzhou University Department of Mechanical Engineering Fuzhou350108 China Institute of Automation Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex Systems Beijing100190 China Institute of Automation Chinese Academy of Sciences Key Laboratory of Cognition and Decision Intelligence for Complex Systems Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Guangzhou Shenghui Cleaning Service Co. Ltd. Guangzhou511436 China BIC-ESAT College of Engineering Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics Beijing100871 China

ISBN: (纸本)9781665481090

Regarding the mobile monitoring system in agricultural automation, the outer diameter monitoring of greenhouse vegetables has significant implications for accurately regulating fruit growth and cultivation plans. In this paper, a novel vision-based two-stage outer diameter detection method is proposed, including the segmentation and outer diameter calculation of greenhouse tomato images. To address the issues of multiple tomatoes in a single image and the similarity in color between tomatoes and the background, a YOLOv8 network embedded with convolutional block attention module is constructed for detection and segmentation in the first stage. Additionally, to solve the problem of inaccurate outer diameter detection caused by different tomato poses and pedicles, a defined central axis method is proposed, which can adaptively filter out the maximum outer diameter candidates and calculate accurate values utilizing depth information in the world coordinate system. The backbone network is fine-tuned on the pre-trained YOLOv8 model with 1000 tomato images. Extensive measurement experiments, involving 215 tomatoes in 80 images, is conducted to validate the effectiveness of our proposed approach. Compared to the ground truth, we obtain a measurement error of 4.27 mm, the coefficient of determination value R2 is 0.9349. © 2024 IEEE.

关键词： Fruits

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Remaining Useful Life Prediction of Lithium-ion Batteries Based on Multi-graph-network model

Remaining Useful Life Prediction of Lithium-ion Batteries Ba...

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第43届中国控制会议

作者： Liujun Tao Huaiyu Wu Xiujuan Zheng Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and Technology Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Accurately predicting the Remaining Useful Life(RUL) of lithium-ion batteries is crucial for their safety and reliability, and it's an important issue of concern for battery management systems. The existing RUL prediction is mainly concentrated on a single source characteristics or a single model, and generally only the time features of the battery Health Indicators(HIs) are considered. This article proposes a multi-feature and multi-graph neural network fusion method for predicting the RUL of batteries. First of all, extract HIs from multiple aspects such as voltage, current, temperature curve and other aspects during partial charging and discharging processes, and construct HIs graph. Secondly, preliminary predictions of RUL were made using Graph Convolutional Network(GCN), Graph Attention Network(GAT), and Graph Sample and Aggregate Network(Graph SAGE),respectively. In order to improve the prediction accuracy of the model, the model extracts spatial features from non-homologous sources and constructs an HI graph as the primary input. Inspired by the advantages of multi-model fusion, random forest regression is used for multi model fusion. To verify the effectiveness of the model, comparative experiments were conducted on the Massachusetts institute of Technology(MIT) battery dataset. The results indicate that the proposed method has better accuracy and stronger robustness in RUL prediction.

关键词： Lithium-ion batteries Prediction of remaining useful life Multi source spatial features Multi graph neural network Random forest regression

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Empirical research on robot-Assisted educational innovations 26

Empirical research on robot-Assisted educational innovations

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26th IEEE International Conference on Intelligent engineering systems, INES 2022

作者： Nagy, Eniko Holik, Ildiko Institute of Cyberphysical Systems Obuda University Antal Bejczy Center for Intelligent Robotics John von Neumann Faculty Budapest Hungary Trefort Agoston Centre of Engineering Education Obuda University Kalman Kando Faculty of Electrical Engineering Budapest Hungary

ISBN: (数字)9781665492096

ISBN: (纸本)9781665492096

The technological development of the 21st century entails the methodological renewal of public education and higher education, and the application of educational innovations. As a result of this modernisation, educational robots have also entered the educational field, offering many new possibilities in the areas of curriculum development, motivation of students, interest arousal and soft skills development. Tutor robots are also being used successfully in education in Hungary, mainly in the field of programming education. In our questionnaire survey we explored the characteristics of robot-supported educational innovations. The paper presents the main results of the research. © 2022 IEEE.

关键词： Surveys

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Diffusion-Based mmWave Radar Point Cloud Enhancement Driven by Range Images

arXiv

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arXiv 2025年

作者： Wu, Ruixin Li, Zihan Wang, Jin Xu, Xiangyu Yu, Huan Zheng, Zhi Huang, Kaixiang Lu, Guodong The State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310058 China Zhejiang Key Laboratory of Industrial Big Data and Robot Intelligent Systems Zhejiang University Hangzhou310058 China Robotics Research Center of Yuyao City Ningbo315400 China State Key Laboratory of Robotics and Systems Department of Mechatronics Engineering Harbin Institute of Technology Harbin150001 China

Millimeter-wave (mmWave) radar has attracted significant attention in robotics and autonomous driving. However, despite the perception stability in harsh environments, the point cloud generated by mmWave radar is relatively sparse while containing significant noise, which limits its further development. Traditional mmWave radar enhancement approaches often struggle to leverage the effectiveness of diffusion models in super-resolution, largely due to the unnatural range-azimuth heatmap (RAH) or bird’s eye view (BEV) representation. To overcome this limitation, we propose a novel method that pioneers the application of fusing range images with image diffusion models, achieving accurate and dense mmWave radar point clouds that are similar to LiDAR. Benefitting from the projection that aligns with human observation, the range image representation of mmWave radar is close to natural images, allowing the knowledge from pre-trained image diffusion models to be effectively transferred, significantly improving the overall performance. Extensive evaluations on both public datasets and self-constructed datasets demonstrate that our approach provides substantial improvements, establishing a new state-of-the-art performance in generating truly three-dimensional LiDAR-like point clouds via mmWave radar. Copyright © 2025, The Authors. All rights reserved.

关键词： Radar imaging

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Estimation of the Raya UUV Hydrodynamic Coefficients Using OpenFOAM

Estimation of the Raya UUV Hydrodynamic Coefficients Using O...

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OCEANS

作者： João Leitão Pedro Pereira Raul Campilho Andry Pinto Centre for Robotics and Automation Systems of INESC TEC (CRAS) CIDEM School of Engineering Polytechnic of Porto (ISEP) Faculty of Engineering University of Porto (FEUP) Institute of Science and Innovation in Mechanical and Industrial Engineering (INEGI) Porto Portugal

ISBN: (数字)9798331540081

ISBN: (纸本)9798331540098

Accurate dynamics modelling of Unmanned Under-water Vehicles (UUV s) is critical for optimizing mission planning, minimizing collision risks, and ensuring the successful execution of tasks in diverse underwater environments. This paper presents a structured approach to estimating the hydrodynamic coeffi-cients of UUV s. Initially, it follows a detailed methodology for estimating hydrodynamic coefficients using simple geometries, a sphere and a spheroid, using the Computational Fluid Dy-namics (CFD) software OpenFoam, and comparing the results to analytical solutions, enabling the validation of the simulations approach. Following this, the paper provides an in-depth analysis of the damping and added mass coefficients for the Raya UUV, offering valuable insights into its hydrodynamic behaviour.

关键词： Geometry Damping Analytical models Accuracy Fluids Oceans Hydrodynamics Software Planning Vehicle dynamics

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Implementation of Rev1 and Rev2 Bug Family Algorithms in ROS Noetic

Implementation of Rev1 and Rev2 Bug Family Algorithms in ROS...

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Information, Control, and Communication Technologies (ICCT), International Conference on

作者： Maksim Roslavtsev Alexander Eryomin Ramil Safin Evgeni Magid Department of Computer Engineering (DCE) Moscow Institute of Electronics and Mathematics Higher School of Economics Moscow Russian Federation Laboratory of Intelligent Robotics Systems (LIRS) Institute of Information Technology and Intelligent Systems Kazan Federal University Kazan Russian Federation

ISBN: (数字)9798331517564

ISBN: (纸本)9798331517571

Modern map-dependent algorithms for mobile robot navigation typically overload a CPU and memory with a gradually increasing amount of environmental data. In contrast, Bug family local path planning algorithms operate without mapping and have significantly lower hardware requirements. Bug algorithms use real-time measurements from visual and touch sensors to make immediate decisions on direction of the robot’s motion. This paper presents an implementation of Rev1 and Rev2 Bug algorithms for the Robot Operating System (ROS) Noetic framework with a virtual model of the TurtleBot3 Burger robot. Given algorithms are validated in Gazebo simulation using various convex and maze environments. The results demonstrate superiority of Rev1 method over Rev2 in trajectory length in convex maps. However, Rev2 finds shorter paths in maze type environments.

关键词： Visualization Navigation Operating systems Computer bugs Tactile sensors Real-time systems Trajectory Motion measurement Robots Testing

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