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SSRN 2024年

作者： Zhou, Bei Hu, Cheng Zeng, Jun Shi, Yao Xie, Lei Su, Hongye The State Key Laboratory of Industrial Control Technology Zhejiang University 38 Zheda Road Xihu District Hang zhou Zhejiang310027 China Hybrid Robotics Group the Department of Mechanical Engineering UC Berkeley United States

Drift vehicle control offers valuable insights to support safe autonomous driving in extreme conditions, which hinges on tracking a particular path while maintaining the vehicle states near the drift equilibrium points (DEP). However, conventional tracking methods are not adaptable for drift vehicles due to their opposite steering angle and yaw rate. In this paper, we propose an adaptive path tracking (APT) control method to dynamically adjust drift states to follow the reference path, improving the commonly utilized predictive path tracking methods with released computation burden. Furthermore, existing control strategies necessitate a precise system model to calculate the DEP, which can be more intractable due to the highly nonlinear drift dynamics and sensitive vehicle parameters. To tackle this problem, an adaptive learning-based model predictive control (ALMPC) strategy is proposed based on the APT method, where an upper-level Bayesian optimization is employed to learn the DEP and APT control law to instruct a lower-level MPC drift controller. This hierarchical system architecture can also resolve the inherent control conflict between path tracking and drifting by separating these objectives into different layers. The ALMPC strategy is verified on the Matlab-Carsim platform, and simulation results demonstrate its effectiveness in controlling the drift vehicle to follow a clothoid-based reference path even with the misidentified road friction parameter. © 2024, The Authors. All rights reserved.

关键词： Model predictive control

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Analysis of YouTube Video Comments with NLP Methods

Analysis of YouTube Video Comments with NLP Methods

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International Conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Pirnau Mironela Priescu Iustin Priescu Catalina Mihaela Pirnau Claudiu Ghiculescu Liviu Daniel Department of Informatics Faculty of Informatics “Titu Maiorescu” University Bucharest Romania Faculty of Automatic Control and Computer Science National University of Science and Technology POLITEHNICA Bucharest Bucharest Romania Manufacturing Engineering Department Faculty of Industrial Engineering and Robotics National University of Science and Technology POLITEHNICA Bucharest Bucharest Romania

ISBN: (数字)9798350371154

ISBN: (纸本)9798350371161

This study proposes methods that can be used to examine and interpret comments that users have made after watching videos on YouTube on a particular topic. YouTube tutorials are very popular among young people. They have become an important pillar in informal education, thus contributing to the rapid acquisition of skills and knowledge. Under these circumstances, we were interested in analysing the YouTube videos comments, knowing that the platform has a continuous increase in popularity, which is also due to the opportunities of sharing them. Since ChatGPT-themed YouTube videos have seen a significant surge in popularity since 2022, we were interested to analyse some videos that approach the topics of “ChatGPT, AI clone, AI robot and Deep Learning.”

关键词： Video on demand Social networking (online) Education Tutorials Chatbots Web sites Artificial intelligence

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Invisible Servoing: a Visual Servoing Approach with Return-Conditioned Latent Diffusion

arXiv

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arXiv 2024年

作者： Gerges, Bishoy Bazzana, Barbara Botteghi, Nicolò Aboudorra, Youssef Franchi, Antonio Robotics and Mechatronics Group Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede7500AE Netherlands Department of Applied Mathematics University of Twente Enschede7500AE Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome00185 Italy

In this paper, we present a novel visual servoing (VS) approach based on latent Denoising Diffusion Probabilistic Models (DDPMs). Opposite to classical VS methods, the proposed approach allows reaching the desired target view, even when the target is initially not visible. This is possible thanks to the learning of a latent representation that the DDPM uses for planning and a dataset of trajectories encompassing target-invisible initial views. The latent representation is learned using a Cross-Modal Variational Autoencoder, and used to estimate the return for conditioning the trajectory generation of the DDPM. Given the current image, the DDPM generates trajectories in the latent space driving the robotic platform to the desired visual target. The approach is applicable to any velocity-based controlled platform. We test our method with simulated and real-world experiments using generic multi-rotor Uncrewed Aerial Vehicles (UAVs). A video of our experiments can be found at https://***/yu-aTxqceOA. Copyright © 2024, The Authors. All rights reserved.

关键词： Trajectories

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Forward Kinematics Development of a 3-RRS Parallel Manipulator for Real-Time control

Forward Kinematics Development of a 3-RRS Parallel Manipulat...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： S. Ali A. Moosavian Omid Mahdizadeh Sina Hallajian Sara Ashrafi Mohammad Jamali Vahid Akbari Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems (ARAS) Lab. K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781665454537

In control of parallel robots, forward kinematics calculation is mainly required. In some studies, obtained equations are solved numerically with massive calculations that is not acceptable for control implementations. This paper introduces a new method to extract forward kinematics for a 3- RRS robot. This method calculates the kinematics of passive joints with two separated equations, which can be solved to decrease the total computation demands. Also, a new weight compensation mechanism is proposed to improve the dynamic response by a linear pneumatic actuator placed between the ground and the end-effector. On the other hand, to use various control algorithms, the position of the rolling ball on the end- effector (moving platform) must be measured. This is performed using Convolutional Neural Networks (CNNs) as image processing algorithms. Since the system must work quickly for a high-frequency task, the proposed image processing algorithm can provide the desired fast feedback. Experimental results reveal the merits of the above-described proposed modules.

关键词： Pneumatic actuators Image processing Heuristic algorithms Kinematics Position measurement Pneumatic systems Mathematical models

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Extension Principle and controller Design for Nonlinear Systems

Extension Principle and Controller Design for Nonlinear Syst...

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European control Conference (ECC)

作者： Altuğ İftar Farshad Khorrami Department of Electrical and Electronics Engineering Eskişehir Technical University Eskişehir Turkey Department of Electrical and Computer Engineering Control/Robotics Research Laboratory (CRRL) New York University 5 Metrotech Center Brooklyn NY U.S.A.

We generalize the principle of extension and controller design using this principle for nonlinear systems. We first define principles of inclusion and extension for nonlinear time-invariant (NLTI) systems. Thereafter, we present the necessary and sufficient conditions for a system to be an extension of another and show that when the expanded system is an extension of the original system, any controller designed for the expanded system can be contracted for implementation on the original system. Subsequently, we demonstrate how an overlappingly decomposed NLTI system can be expanded so that the expanded system is an extension of the original system, how decentralized controllers can be designed for the expanded system, and how these controllers can be contracted for implementation on the original system. An example is also provided to illustrate the extension and contraction concepts and show controller design using the proposed principles.

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Design of a Parallel Elastic Actuator with a Continuously-Adjustable Equilibrium Position

arXiv

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arXiv 2022年

作者： Chatziandreou, Evangelos Mathews, Chase W. Braun, David J. Advanced Robotics and Control Laboratory Center for Rehabilitation Engineering and Assistive Technology Department of Mechanical Engineering Vanderbilt University NashvilleTN37235 United States

In this paper, we present an adjustable-equilibrium parallel elastic actuator (AE-PEA). The actuator consists of a motor, an equilibrium adjusting mechanism, and a spring arranged into a cylindrical geometry, similar to a motor-gearbox assembly. The novel component of the actuator is the equilibrium adjusting mechanism which (i) does not require external energy to maintain the equilibrium position of the actuator even if the spring is deformed and (ii) enables equilibrium position control with low energy cost by rotating the spring while keeping it undeformed. Adjustable equilibrium parallel elastic actuators resolve the main limitation of parallel elastic actuators (PEAs) by enabling energy-efficient operation at different equilibrium positions, instead of being limited to energy-efficient operation at a single equilibrium position. We foresee the use of AE-PEAs in industrial robots, mobile robots, exoskeletons, and prostheses, where efficient oscillatory motion and gravity compensation at different positions are required. © 2022, CC BY-NC-ND.

关键词： Actuators

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Augmenting Efficient Real-time Surgical Instrument Segmentation in Video with Point Tracking and Segment Anything

arXiv

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arXiv 2024年

作者： Wu, Zijian Schmidt, Adam Kazanzides, Peter Salcudean, Septimiu E. Robotics and Control Laboratory Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada Department of Computer Science Johns Hopkins University BaltimoreMD21218 United States

The Segment Anything Model (SAM) is a powerful vision foundation model that is revolutionizing the traditional paradigm of segmentation. Despite this, a reliance on prompting each frame and large computational cost limit its usage in robotically assisted surgery. Applications, such as augmented reality guidance, require little user intervention along with efficient inference to be usable clinically. In this study, we address these limitations by adopting lightweight SAM variants to meet the efficiency requirement and employing fine-tuning techniques to enhance their generalization in surgical scenes. Recent advancements in Tracking Any Point (TAP) have shown promising results in both accuracy and efficiency, particularly when points are occluded or leave the field of view. Inspired by this progress, we present a novel framework that combines an online point tracker with a lightweight SAM model that is fine-tuned for surgical instrument segmentation. Sparse points within the region of interest are tracked and used to prompt SAM throughout the video sequence, providing temporal consistency. The quantitative results surpass the state-of-the-art semi-supervised video object segmentation method XMem on the EndoVis 2015 dataset with 84.8 IoU and 91.0 Dice. Our method achieves promising performance that is comparable to XMem and transformer-based fully supervised segmentation methods on ex vivo UCL dVRK and in vivo CholecSeg8k datasets. In addition, the proposed method shows promising zero-shot generalization ability on the label-free STIR dataset. In terms of efficiency, we tested our method on a single GeForce RTX 4060/4090 GPU respectively, achieving an over 25/90 FPS inference speed. Code is available at: https://***/wuzijian1997/SIS-PT-SAM © 2024, CC BY.

关键词： Surgical equipment

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Hybrid Unmanned Aerial Underwater Vehicles: A Survey on Concepts and Technologies

SSRN

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SSRN 2023年

作者： Pinheiro, Pedro Miranda Dias de Oliveira Evald, Paulo Jefferson Grando, Ricardo Bedin Neto, Armando Alves Jorge Drews, Paulo Lilles Intelligent Robotics and Automation Group Federal University of Rio Grande Rio Grande Brazil Intelligent Systems and Control Group Federal University of Pelotas Pelotas Brazil Department of Robotics Technological University of Uruguay Rivera Uruguay Department of Electronic Engineering Federal University of Minas Gerais Belo Horizonte Brazil

Hybrid Unmanned Aerial Underwater Vehicle (HUAUV) is a class of multi-modal mobile robots characterized by the ability to fly and navigate underwater, as well as being able to perform the transition between both environments. The development of modern vehicles of this class is driven by the enhancement of mobile robotic systems, sensors, and control techniques. However, the class definition and hierarchy for these vehicles are still vague and undefined. Therefore, this work presents a survey of concepts and prototypes of HUAUVs, developed from 2010 until 2022. The search for works was performed in relevant international conference proceedings and journals. We present a classification of state-of-the-art concepts and prototypes of HUAUVs based on specific main features of vehicles, allowing the identification of trends in HUAUV development, and an actuator-based taxonomy for HUAUVs. Hence, our categorization provides a more cohesive background for future works, as well as a better understanding of the main features of hybrid vehicles. Finally, a pragmatic approach to future applications is provided, given the current trends in Mobile robotics, focusing on unmanned aerial/underwater vehicles. © 2023, The Authors. All rights reserved.

关键词： Antennas

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An Isomerism Learning Model to Solve Time-Varying Problems Through Intelligent Collaboration

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1772-1774页

作者： Zhihao Hao Guancheng Wang Bob Zhang Leyuan Fang Haisheng Li the Department of Computer and Information Science University of MacaoMacao 999078China the School of Data Science the Chinese University of Hong KongShenzhen 518172 Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen 518000 China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China IEEE the College of Electrical and Information Engineering Hunan UniversityChangsha 410082 the Peng Cheng Laboratory Shenzhen 518000China the Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business UniversityBeijing 100048 the School of Computer Science and Engineering Beijing Technology and Business UniversityBeijing 100048China

Dear Editor,This letter deals with a solution for time-varying problems using an intelligent computational(IC)algorithm driven by a novel decentralized machine learning approach called isomerism *** order to meet the challenges of the model’s privacy and security brought by traditional centralized learning models,a private permissioned blockchain is utilized to decentralize the model in order to achieve an effective coordination,thereby ensuring the credibility of the overall model without exposing the specific parameters and solution process.

关键词： ism thereby letter

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Differential Flatness and Manipulation of Elasto-flexible Cables Carried by Aerial Robots in a Possibly Viscous Environment

Differential Flatness and Manipulation of Elasto-flexible Ca...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Chiara Gabellieri Antonio Franchi Robotics and Mechatronics Department Electrical Engineering Mathematics and Computer Science (EEMCS) Faculty University of Twente Enschede The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy LAAS-CNRS Université de Toulouse Toulouse France

This work considers a system composed of two quadrotors manipulating a deformable and extensible cable. The dynamic model is presented, and it is based on a discrete representation of the cable, which is decomposed into lumped masses interconnected by linear springs through passive spherical joints. A set of flat outputs is found for the system. The flatness is exploited to design a method to manipulate the cable, which is then tested through numerical simulations.

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