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2022 International Russian Automation Conference, RusAutoCon 2022

作者： Lipko, Ivan Sevastopol State University Robotics and Intelligent Control Systems Laboratory Sevastopol Russia

ISBN: (数字)9781665466554

ISBN: (纸本)9781665466554

This article is devoted to the identification of the mathematical model of the underwater vehicle MiddleAUV. The central issues of the article are planning and conducting experiments, identifying and comparing simulation results with real data. The experiments were performed inside the pool of the laboratory of robotics and intelligent control systems of Sevastopol State University. Linear motions and circulations were performed at different speeds of rotation of the propellers. The main result obtained in this article is the transfer functions of the horizontal movement of a small autonomous underwater vehicle. The inputs to the transfer functions are the numbers that control propellers' angular velocity and outputs are the angular velocity of the yaw and general velocities during horizontal movement. The movement identification was carried out according to the data received from the onboard navigation module and the built-in bottom video camera. The bottom camera monitors the chessboard located at the bottom of the pool and allows us to get the relative coordinates of device location in the pool. To anyone interested in the identification of underwater vehicles. © 2022 IEEE.

关键词： Transfer functions

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Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

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Petroleum Science 2024年第1期21卷 641-653页

作者： Yun-Peng He Hai-Bo Cheng Peng Zeng Chuan-Zhi Zang Qing-Wei Dong Guang-Xi Wan Xiao-Ting Dong State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016LiaoningChina Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016LiaoningChina Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169LiaoningChina University of Chinese Academy of Sciences Beijing100049China School of Artifcial Intelligence Shenyang University of TechnologyShenyang 110870LiaoningChina

High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well *** learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis ***,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational ***,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different ***,there is heterogeneity in field data,which can dramatically impair the diagnostic *** solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this ***,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC ***,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data ***,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the *** on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational *** the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.

关键词： Sucker-rod pumping system Dynamometer card Working condition recognition Deep learning Time-frequency signature Time-frequency signature matrix

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Method of Forming Paths for Uniform Surface Treatment for Objects of Complex Shape 25

Method of Forming Paths for Uniform Surface Treatment for Ob...

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

作者： Grigorev, Ivan Mursalimov, Eduard Laboratory of Intelligent Information Systems for Marine Robots M.D. Ageev Institute of Marine Technology Problems FEB RAS Vladivostok Russia Laboratory of Robotics and Intelligent Control Systems Sevastopol State University Laboratory of Intelligent Information Systems for Marine Robots M.D. Ageev Institute of Marine Technology Problems FEB RAS Vladivostok Russia

ISBN: (纸本)9798350389234

In most cases, tool impact paths for surface treatment (painting, milling, laser hardening, etc.) represent a set of continuous spatial curves lying on the surface to be treated. For uniform processing, adjacent curves from this set must be equidistant from each other. This paper presents a new method for covering a given polygonal mesh with equidistant lines based on given initial lines (in the form of a set of vertices on this mesh) and a given distance between adjacent lines, that is measured by Euclidean distance. The method is based on constructing spheres from each vertex of the initial line and removing the vertices of the mesh that fall into at least one of the spheres: the desired equidistant line will be represented by not removed vertices lying on the spheres. To construct each subsequent equidistant line, the last constructed line is used as the initial one: thus, the entire mesh is covered along the surface, despite the fact that the distance between adjacent lines is measured in space. Due to this, the proposed method, unlike the existing ones, works with surfaces of any complexity and requires less computing resources. Ordering the points of the constructed lines, to obtain the reference points of the paths that can be executed by the manipulator, is also presented. © 2024 IEEE.

关键词： Spheres

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A Position-Force control Approach for an Underwater Vehicle-Manipulator System

A Position-Force Control Approach for an Underwater Vehicle-...

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2023 International Conference on Ocean Studies, ICOS 2023

作者： Kabanov, Aleksey A. Dementiev, Kirill V. Sevastopol State University Department of Informatics and Control in Technical Systems Sevastopol Russia Sevastopol State University Robotics and Intelligent Control System Laboratory Sevastopol Russia

ISBN: (纸本)9798350382457

The paper proposes an approach to position-force control in the underwater vehicle-manipulator systems. There are two different strategies to realize position-force control systems: through a decoupled or coupled controller. The first one is more flexible and is used in the present article as a PID-controllers array. The paper considers the generalized system design methodology applicable to control objects of any kinematic structure. Compensation blocks for manipulator disturbances and calculation of additional end-effector offset to maintain a constant force on the operating point are proposed. The system also utilizes the desired underwater vehicle position calculation based on the relativity of the vehicle position and operating point for a heading set point. The modeling results showed that the system is able to perform qualitatively force operations in a given point of the working space. In addition, the graphs revealed the compensator unit efficiency and confirmed the necessity of the additional offset calculation unit. © 2023 IEEE.

关键词： Manipulators

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6-DOF AUV Identification with MIMO-NARX

6-DOF AUV Identification with MIMO-NARX

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2023 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2023

作者： Kabanov, Aleksey A. Lipko, Ivan Y. Dementiev, Kirill V. Sevastopol State University Department of Informatics and Control in Technical Systems Sevastopol Russia Sevastopol State University Robotics and Intelligent Control System Laboratory Sevastopol Russia

ISBN: (纸本)9781665475952

This paper applies the MIMO NARX neural model to identify AUV with six degrees of freedom. Strongly nonlinear dependencies are modeled using a MIMO NARX model trained using «input-output» experimental data. This results in a grey box model with a partially known internal structure that can be supervised. This is achieved by specifying a certain regressors type, which is feedback to the model input. Obtained results show that the neural model trained by the Levenberg-Marquardt numerical algorithm provides acceptable performance and accuracy. Validation of the model was performed using data from full-scale experiments, which allowed to identify the weaknesses and advantages of the resulting system more accurately. © 2023 IEEE.

关键词： Degrees of freedom (mechanics)

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Path Planning with Potential Field-Based Obstacle Avoidance in a 3D Environment by an Unmanned Aerial Vehicle

arXiv

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arXiv 2023年

作者： Batinovic, Ana Goricanec, Jurica Markovic, Lovro Bogdan, Stjepan University of Zagreb Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems Unska 3 Zagreb10000 Croatia

In this paper we address the problem of path planning in an unknown environment with an aerial robot. The main goal is to safely follow the planned trajectory by avoiding obstacles. The proposed approach is suitable for aerial vehicles equipped with 3D sensors, such as LiDARs. It performs obstacle avoidance in real time and on an on-board computer. We present a novel algorithm based on the conventional Artificial Potential Field (APF) that corrects the planned trajectory to avoid obstacles. To this end, our modified algorithm uses a rotation-based component to avoid local minima. The smooth trajectory following, achieved with the MPC tracker, allows us to quickly change and re-plan the UAV trajectory. Comparative experiments in simulation have shown that our approach solves local minima problems in trajectory planning and generates more efficient paths to avoid potential collisions with static obstacles compared to the original APF method. © 2023, CC BY-SA.

关键词： Motion planning

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Design and Validation of a Wireless Drone Docking Station

arXiv

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arXiv 2023年

作者： Stuhne, Dario Vasiljević, Goran Bogdan, Stjepan Kovačić, Zdenko LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 Zagreb10000 Croatia

Drones are increasingly operating autonomously, and the need for extending drone power autonomy is rapidly increasing. One of the most promising solutions to extend drone power autonomy is the use of docking stations to support both landing and recharging of the drone. To this end, we introduce a novel wireless drone docking station with three commercial wireless charging modules. We have developed two independent units, both in mechanical and electrical aspects: the energy transmitting unit and the energy receiving unit. We have also studied the efficiency of wireless power transfer and demonstrated the advantages of connecting three receiver modules connected in series and parallel. We have achieved maximum output power of 96.5 W with a power transfer efficiency of 56.6% for the series connection of coils. Finally, we implemented the system in practice on a drone and tested both energy transfer and landing. Copyright © 2023, The Authors. All rights reserved.

关键词： Drones

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Brain over Brawn: Using a Stereo Camera to Detect, Track, and Intercept a Faster UAV by Reconstructing the Intruder's Trajectory

Field Robotics

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Field robotics 2025年 2卷 222-240页

作者： Antonella Barišić Frano Petric Stjepan Bogdan Laboratory for Robotics and Intelligent Control Systems Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 Zagreb Croatia

This paper presents our approach to intercepting a faster intruder UAV, inspired by the MBZIRC 2020 Challenge 1. By utilizing a priori knowledge of the shape of the intruder's trajectory, we can calculate an interception point. Target tracking is based on image processing by a YOLOv3 Tiny convolutional neural network, combined with depth calculation using a gimbal-mounted ZED Mini stereo camera. We use RGB and depth data from the camera, devising a noise-reducing histogram-filter to extract the target's 3D position. Obtained 3D measurements of target's position are used to calculate the position, orientation, and size of a figure-eight shaped trajectory, which we approximate using a Bernoulli lemniscate. Once the approximation is deemed sufficiently precise, as measured by the distance between observations and estimate, we calculate an interception point to position the interceptor UAV directly on the intruder's path. Our method, which we have significantly improved based on the experience gathered during the MBZIRC competition, has been validated in simulation and through field experiments. Our results confirm that we have developed an efficient, visual-perception module that can extract information describing the intruder UAV's motion with precision sufficient to support interception planning. In a majority of our simulated encounters, we can track and intercept a target that moves 30% faster than the interceptor. Corresponding tests in an unstructured environment yielded 9 out of 12 successful results.

关键词： Autonomous aerial vehicles Trajectory Target tracking Cameras Three-dimensional displays Robots Radar tracking Image reconstruction Estimation Detectors

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Bio-inspired visual relative localization for large swarms of UAVs

Bio-inspired visual relative localization for large swarms o...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Martin Křížek Matouš Vrba Antonella Barišić Kulaš Stjepan Bogdan Martin Saska Faculty of Electrical Engineering Czech Technical University in Prague Prague Laboratory for Robotics and Intelligent Control Systems (LARICS) Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

We propose a new approach to visual perception for relative localization of agents within large-scale swarms of Unmanned Aerial Vehicles (UAVs). Inspired by biological perception utilized by schools of sardines, swarms of bees, and other large groups of animals capable of moving in a decentralized yet coherent manner, our method does not rely on detecting individual neighbors by each agent and estimating their relative position, but rather we propose to regress a neighbor density over distance. This allows for a more accurate distance estimation as well as better scalability with respect to the number of neighbors. Additionally, a novel swarm control algorithm is proposed to make it compatible with the new relative localization method. We provide a thorough evaluation of the presented methods and demonstrate that the regressing approach to distance estimation is more robust to varying relative pose of the targets and that it is suitable to be used as the main source of relative localization for swarm stabilization.

关键词： Location awareness Visualization Scalability Estimation Object detection Autonomous aerial vehicles Robustness

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Autonomous, Mobile Manipulation in a Wall-Building Scenario: Team larics at MBZIRC 2020

Field Robotics

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Field robotics 2025年 2卷 201-221页

作者： Ivo Vatavuk Marsela Polic Ivan Hrabar Frano Petric Matko Orsag Stjepan Bogdan Laboratory for Robotics and Intelligent Control systems University of Zagreb Faculty of Electrical Engineering and Computing Unska 3 Zagreb Croatia

In this paper we present our hardware design and control approaches for a mobile manipulation platform used in Challenge 2 of the MBZIRC 2020 competition. In this challenge, a team of UAVs and a single UGV collaborate in an autonomous, wall-building scenario, motivated by construction automation and large-scale robotic 3D printing. The robots must be able, autonomously, to detect, manipulate, and transport bricks in an unstructured, outdoor environment. Our control approach is based on a state machine that dictates which controllers are active at each stage of the Challenge. In the first stage our UGV uses visual servoing and local controllers to approach the target object without considering its orientation. The second stage consists of detecting the object's global pose using OpenCV-based processing of RGB-D image and point-cloud data, and calculating an alignment goal within a global map. The map is built with Google Cartographer and is based on onboard LIDAR, IMU, and GPS data. Motion control in the second stage is realized using the ROS Move Base package with Time-Elastic Band trajectory optimization. Visual servo algorithms guide the vehicle in local object-approach movement and the arm in manipulating bricks. To ensure a stable grasp of the brick's magnetic patch, we developed a passively-compliant, electromagnetic gripper with tactile feedback. Our fully-autonomous UGV performed well in Challenge 2 and in post-competition evaluations of its brick pick-and-place algorithms.

关键词： Robots Robot kinematics Navigation Manipulators Cameras Buildings Grippers Automation Service robots Laser radar

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