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检索条件"任意字段=3rd International Conference on Intelligent Robotics and Control Engineering, IRCE 2020"

共 1399 条记录，以下是11-20 订阅

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2020 3rd international conference on robotics, control and Automation engineering, RCAE 2020

2020 3rd International Conference on Robotics, Control and A...

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3rd international conference on robotics, control and Automation engineering, RCAE 2020

ISBN: (纸本)9781728186382

The proceedings contain 23 papers. The topics discussed include: an approach to the analysis and design of fuzzy control system;design of a PID control system for a wastewater treatment plant;research on voltage control of P2.5 hybrid system;discussion on a new design of overhead transmission line inspection robot;anti-disturbance control of vertical pitch attitude of underwater spherical robot;an improved trajectory learning algorithm based on DMPs;cooperative encirclement in swarm robotics based on triangle antenna model;path planning and tracking strategy under emergency for vehicle obstacle avoidance system;design of a PID control system for a wastewater treatment plant;an approach to the analysis and design of fuzzy control system;absolute stability for a class of Takagi-Sugeno fuzzy control systems;energy efficient pivot steering control of differential steering vehicle;and research on power market user credit evaluation based on k-means clustering and contour coefficient.

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A Self-Aware Robotic Machining Architecture Based on Physics-Informed Neural Networks

A Self-Aware Robotic Machining Architecture Based on Physics...

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Mechatronics, control and robotics (ICMCR), international conference on

作者： Yuanhui Zhang Mingfeng Wang Kai Wu Shien-Ming Wu School of Intelligent Engineering South China University of Technology Guangzhou China Department of Mechanical and Aerospace Engineering Brunel University London UK

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

Industrial robots have been widely used in various industrial scenarios due to their flexibility and expandability. However, robots are susceptible to instability at high speeds and load conditions due to their low stiffness and dynamic characteristics variation with posture. Enhancing the processing stability of industrial robots through data-driven modeling and physical modeling approaches suffers from different drawbacks, such as solution complexity and weak interpretability. With the emergence of physics-informed neural networks (PINNs), new methodologies can be developed to enhance the self-aware processing of robots. In this paper, typical industry application scenarios and dynamics of robotics as well as PINNs are introduced and analyzed, and a framework and method based on PINNs are proposed to enhance the self-aware operation of industrial robots. This framework and methodology contribute to the researcher's efforts to apply PINNs more intensively to robot operation in the future to improve the stability and intelligence of robot operation.

关键词： Mechatronics Service robots Neural networks Machining Milling Industrial robots Prediction algorithms Stability analysis Thermal stability Self-aware

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Detection and Mitigation of DDOS Attack in SDN Using Feature Based RF & MLP Approach

Detection and Mitigation of DDOS Attack in SDN Using Feature...

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intelligent Data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： Saranraj K Sumugar M Anantha Moorthy R Gowthami N S. Tamilselvi Information Technology National Engineering College Kovilpatti India Electronics and Communication Engineering National Engineering College Kovilpatti India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

Software Defined Networking (SDN) is an architecture that decouples the control plane from the data plane, allowing for centralized oversight and flexible configuration of network resources via software. However, this centralization of the controller makes it especially susceptible to Distributed Denial of Service (DDoS) attacks.. To effectively prevent and mitigate such attacks, deploying a robust machine learning model is crucial. In this project, the Genetic Algorithm and Chimp Optimization Algorithm were employed as optimal feature selection methods to identify and extract the most representative and distinguishing features from the SDN_DDoS_2020 dataset, which contains ICMP, TCP, and UDP attack traffic (sourced from Mendeley). The refined feature subset was then used to train and evaluate the performance of two machine learning algorithms commonly used are Random Forest (RF) and Multilayer Perceptron (MLP). Furthermore, a dedicated mitigation model was developed to block or redirect the flood requests from TCP, UDP, and ICMP attack traffic. Among the models tested, the combination of the Chimp Optimization Algorithm with the MLP classifier demonstrated superior performance, achieving an impressive accuracy of 98.68%. Notably, this model also exhibited a low false alarm rate of 0.74 compared to all other models, enhancing its reliability in real world scenarios where accurate attack detection and minimal false positives are essential.

关键词： Accuracy Machine learning algorithms Prevention and mitigation Feature extraction Denial-of-service attack Software defined networking Computer crime Protection Optimization Classification tree analysis

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Trajectory Tracking of a Nonholonomic Mobile Robot using Optimal Cascade Sliding Mode controller 3

Trajectory Tracking of a Nonholonomic Mobile Robot using Opt...

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3rd international conference on intelligent robotics and control engineering (irce)

作者： Chatterjee, Medha Hanif, Omar Deshpande, Nihar G. Stancu, Alexandra Univ Manchester Dept Elect & Elect Engn Manchester Lancs England Univ Manchester Sch Mech Aerosp Civil Engn Manchester Lancs England

ISBN: (纸本)9781728189727

The trajectory tracking for a non-holonomic mobile robot is addressed in this paper. Cascade control is implemented with a Sliding Mode controller for the outer loop and a Proportional-Integral-Derivative controller governing the inner loop. Linear Quadratic Regulator is further applied to the outer loop to optimize the controller's effort. The model is further analyzed based on various output performances such as trajectory tracking, reference tracking of linear and angular velocities, sliding surfaces of the controller, and its robustness. A comparative analysis with and without an optimal approach has been illustrated. Simulations are carried out on a virtual robotic simulator in LabVIEW.

关键词： nonholonomic mobile robot trajectory tracking lyapunov stability Sliding Mode control (SMC) cascade control Linear Quadratic Regulator (LQR) NI LabVIEW

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Application of Surface Reconstruction for Car Undercarriage Inspection 3

Application of Surface Reconstruction for Car Undercarriage ...

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3rd international conference on intelligent robotics and control engineering (irce)

作者： Dorfler, Martin Pivonka, Tomas Kosnar, Karel Preucil, Libor Czech Tech Univ CIIRC Jugoslavskych Partyzanu 3 Prague 6 Czech Republic

ISBN: (纸本)9781728189727

The method for camera-based 3D reconstruction of car undercarriages is proposed in this paper. It is designed for a special scanner, which is placed under a road level and scans undercarriages of passing cars. The scanner uses mirrors to increase a distance from a camera and to capture a stereo image only by one camera. The 3D models of individual parts of an undercarriage are reconstructed by a correlation-based block-matching algorithm. Afterward, these models are stitched together based-on visual odometry. The method was successfully tested on real car undercarriages.

关键词： stereo reconstruction computer vision visual odometry

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An Improved intelligent Scissors Algorithm for the Segmentation of Vessels Segments in Coronary Angiography Imaging 3

An Improved Intelligent Scissors Algorithm for the Segmentat...

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3rd international conference on intelligent robotics and control engineering (irce)

作者： Li, Yue Pan, Hangyi Jiang, Lurong Tong, Jijun Shen, Yuqiang Zhejiang Sci Tech Univ Hangzhou 310018 Peoples R China Zhejiang Univ Affiliated Hosp 4 Sch Med Hangzhou 310018 Peoples R China

ISBN: (纸本)9781728189727

Interactive segmentation is widely used to precisely segment the parts of interest in medical images. Among them, the intelligent scissors algorithm is an efficient interactive segmentation algorithm, but it has poor performance in processing images with a high similarity between foreground and background. And it is easily affected by the strong edge, which leads to more seed points and longer time to segment the interested vessel segments in the coronary angiography images. In order to improve the segmentation efficiency, we redesign the cost function, using Canny operator, Scharr operator, to replace the Laplace operator in the traditional algorithm. Moreover, gradient magnitude adjustment function and histogram adjustment function are introduced to improve the segmentation effect. Experiment results show that the improved algorithm can shorten the segmentation time and improve the segmentation efficiency without the loss of performance compared with the traditional algorithm.

关键词： intelligent scissors live-wire interactive image segmentation medical image processing

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Swarm-Sim: A 2D & 3D Simulation Core for Swarm Agents 3

Swarm-Sim: A 2D & 3D Simulation Core for Swarm Agents

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3rd international conference on intelligent robotics and control engineering (irce)

作者： Cheraghi, Ahmad Reza Actun, Karol Shahzad, Sahdia Graffi, Kalman Heinrich Heine Univ Dusseldorf Technol Social Networks Dusseldorf Germany Honda Res Inst Europe GmbH Offenbach Germany

ISBN: (数字)9781728189727

ISBN: (纸本)9781728189727

(Robot) swarm networks are consisting of magnitudes of individual agents that are capable to move in a world and interact with each other or with passive items. Through local, individual algorithms applied in the agents desired properties of the swarm can emerge. In this paper, we present Swarm-Sim, a round-based simulator that supports the evaluation of such large scaled swarms in a 2D and 3D world. Agents can move in the simulated world, perceive their surroundings, carry other agents and items, as well as communicate with the position they stand on through pheromones or markings as well as with other agents and items in this world. Through this, many swarm-related use cases are supported. Implementing swarm algorithms is easy as the simulator is completely written in python and its code is open source. This allows also to simulate large swarms due to the good performance of the simulator. Thorough analysis of the swarm behavior is supported through plots and visualizations.

关键词： Swarm Agent 2D Simulator 3D Simulator Evaluation Tool

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Simulation of Autonomous UAV Navigation with Collision Avoidance and Space Awareness 3

Simulation of Autonomous UAV Navigation with Collision Avoid...

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3rd international conference on intelligent robotics and control engineering (irce)

作者： Li, Jian He, Hongmei Tiwari, Ashutosh Cranfield Univ Sch Aerosp Transport & Mfg Cranfield Beds England Univ Sheffield Dept Automat Control & Syst Engn Sheffield S Yorkshire England

ISBN: (纸本)9781728189727

This research developed a safe navigation system of an autonomous UAV within a comprehensive simulation framework. The navigation system can find a collision-free trajectory to a randomly assigned 3D target position without any prior map information. It contains four main components: mapping, localization, cognition, and control. The cognition system makes execution command based on the perceived position information about obstacles and the UAV from mapping and localization system. The control system is responsible for executing the input command made by the cognition system. Three case studies for real-life scenarios, such as space awareness, static obstacle avoidance, and dynamic obstacle avoidance, are conducted. The experiments demonstrate that the UAV can determine a collision-free trajectory under all three cases of environments. All simulated components are designed to match their real-world counterparts' dynamics and properties. Ideally, the simulated navigation framework can be transferred to a real UAV without any changes. As the navigation system is implemented modularly, it is easier to test and validate to ensure its performance. Moreover, the system has excellent readability, maintainability, and extensibility. Hence, the simulation framework provides an excellent platform for future robotic research.

关键词： autonomous navigation dynamic obstacle avoidance offline navigation path planning restricted area avoidance safe navigation simulation space awareness static obstacle avoidance

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Apply PSO Algorithm with Searching Space Improvements on a 5 Degrees of Freedom Robot 3

Apply PSO Algorithm with Searching Space Improvements on a 5...

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3rd international conference on intelligent robotics and control engineering, irce 2020

作者： Nguyen, Thanh-Trung Tao, Ngoc-Linh Nguyen, Van-Tinh Bui, Ngoc-Tam Nguyen, V.H Watanabe, Dai School of Mechanical Engineering Hanoi University of Science and Technology No1 Dai Co Viet Road Ha Noi Viet Nam Shibaura Institute of Technology Department of Machinery and Control System 307 Fusaku Minuma-ku Saitama City Japan

ISBN: (纸本)9781728189727

In this research, Particle Swarm Optimization (PSO) algorithm has been applied to solve the Inverse Kinematic (IK) problem for redundant serial manipulator robots. The new point of the study is to consider the continuity of the joints' variable. By noting this problem, the process of solving the Inverse Kinematic problem for the robots by the optimal algorithm has been significantly improved in terms of accuracy, execution time, and standard deviation (STD) as well as the number of iterations needed. The algorithm has been applied to solve the Inverse Kinematic problem on the 5-Degree of Freedom 5R robot model. The results show that just using the PSO algorithm with the above search domain limit has improved the quality of IK process. © 2020 IEEE.

关键词： Inverse kinematics

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Stereo Visual Inertial Mapping Algorithm for Autonomous Mobile Robot 3

Stereo Visual Inertial Mapping Algorithm for Autonomous Mobi...

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3rd international conference on intelligent robotics and control engineering (irce)

作者： Zhang, Mi Han, Songshan Wang, Shihan Liu, Xing Hu, Mengyu Zhao, Jiayang Beijing Sineva Technol Co Ltd Beijing 100176 Peoples R China Zhejiang Sineva Intelligent Technol Co Ltd Haining 314400 Zhejiang Peoples R China

ISBN: (纸本)9781728189727

Simultaneous Localization and Mapping (SLAM) is a fundamental problem for autonomous mobile robots (AMRs). AMRs are widely used in automated warehousing, factory material transfer systems, flexible assembly systems, and other intelligent transportation sites. The visual Inertial Odometry (VIO) which consists of the camera and inertial-measurement-unit (IMU), is a popular approach to achieve accurate 6-DOF state estimation. However, such locally accurate VIO is prone to drift and cannot provide a global consistent map. The prerequisite for re-localizing the robot and ensuring precise autonomous navigation is an accurate and global consistent map of its environment. In this study, we propose a stereo visual-inertial mapping system. The front-end is a robust stereo VIO based on a tightly-coupled sliding window optimization. The core of the back-end is the global Bundle-Adjustment (BA) which is a nonlinear optimization, in which IMU is also added as a time-domain constraint. Meanwhile, stereo-camera-IMU extrinsic calibration is performed in BA to improve mapping accuracy. The selection principles of keyframes and map points are also designed according to the AMRs application characteristics. Further, the forward and backward Perspective-n-Point (PNP) method is also adopted to avoid the loop-detection mismatch. The performance of the system was validated and compared against other state-of-the-art algorithms. The findings revealed the effectiveness and robustness of this stereo visual-inertial mapping algorithm.

关键词： visual inertial mapping stereo camera AMR SLAM

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