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Retinal disorder diagnosis based on hybrid deep learning models

Multimedia Tools and Applications 2025年 1-25页

作者： Sedik, Ahmed El-Shafai, Walid El-Hag, Noha A. El-Banby, Ghada M. Abd El-Samie, Fathi E. Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafrelsheikh University Kafr el-Sheikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Algarbia Al Mahalla Al Kubra31951 Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Anomaly detection from medical images is badly needed for automated diagnosis. For example, medical images obtained with several modalities, such as magnetic resonance (MR) and confocal microscopy, need to be classified for anomaly detection. The MR images may contain tumors that need to be detected with anomaly detection techniques. In MR imaging, brain tumors are represented as areas composed of abnormal cells that need to be detected. On the other hand, confocal microscopy can be used for retinal imaging. Hence, there is a need to apply classification techniques for diagnosing diseases of the eye, such as Diabetic Retinopathy (DR), which leads to exudates in different regions of the retina. The detection of exudates is necessary for the diagnosis of DR. In this paper, two models are presented for the classification of MR and retinal images. Much research has been done in this area, but it did not achieve high accuracy of classification in an acceptable time. In addition, the previous models did not consider both types of image modalities considered in this paper. The suggested models are Convolutional Neural Network (CNN) and Convolutional Long Short-Term Memory (Conv-LSTM). They are used to classify normal and abnormal cases of both brain tumor and DR diseases. The CNN model is composed of six convolutional layers and six max-pooling layers. A soft-max activation function takes the classification decision. The proposed Conv-LSTM model is composed of three stages: pre-processing, feature extraction, and classification. The deep learning model performance is better than those of traditional networks. The CNN gives an accuracy of 94.26% for DR classification and 95.8% for brain tumor classification, while the Conv-LSTM gives the maximum accuracy of 96.41% for DR classification and 97.4% for brain tumor classification. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Confocal microscopy

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AI Enabled Automatic Mobile Robot intelligent Navigation in Construction with Obstacle Awareness

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IEEE Transactions on Automation Science and Engineering 2025年

作者： Zhang, Yinlong Liu, Yuanhao Cui, Yunge Zeng, Ziming Liang, Wei Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China University of Chinese Academy of Sciences Beijing101408 China Zeekr Group Zeekr Intelligent Driving Department Shanghai110078 China Shenzhen Polytechnic University School of Automotive and Transportation Engineering Shenzhen518055 China

In the construction industry, the integration of artificial intelligence (AI) and robotics has led to significant advancements in automating various tasks. One critical aspect is the intelligent navigation of automatic mobile robot (AMR) within construction sites, where dynamic environments pose challenges such as inaccurate robot state estimation, irregular and textureless obstacle detection. To solve these issues, this paper designs an AI enabled obstacle-aware AMR intelligent navigation approach while ensuring robot safety and efficiency. Specifically, the robot is equipped with the complementary RGB camera, inertial measurement unit (IMU) and wheel encoder to estimate the states (i.e., positions, orientations and velocities), which have been tightly fused in the optimization framework. Furthermore, the RGB-Depth images are jointly fed into the AI model. It combines of Mask-RCNN and multi-scale attention network, to detect and segment the obstacles, and estimate the corresponding relative depth. It should be noted that the system incorporates obstacle awareness mechanisms to dynamically switch the robot's velocities in response to obstacles in the environment, ensuring smooth and collision-free movement. Experimental results demonstrate the effectiveness and robustness of the proposed AI-enabled navigation system in real-world construction scenarios, showcasing its potential to enhance productivity and safety in construction automation. © 2004-2012 IEEE.

关键词： Construction industry

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Polytope Volume Monitoring Problem: Formulation and Solution via Parametric Linear Program Based control Barrier Function

arXiv

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arXiv 2025年

作者： Wu, Shizhen Dong, Jinyang Fang, Xu Sun, Ning Fang, Yongchun Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin300353 China The Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China

Motivated by the latest research on feasible space monitoring of multiple control barrier functions (CBFs) as well as polytopic collision avoidance, this paper studies the Polytope Volume Monitoring (PVM) problem, whose goal is to design a control law for inputs of nonlinear systems to prevent the volume of some state-dependent polytope from decreasing to zero. Recent studies have explored the idea of applying Chebyshev ball method in optimization theory to solve the case study of PVM;however, the underlying difficulties caused by nonsmoothness have not been addressed. This paper continues the study on this topic, where our main contribution is to establish the relationship between nonsmooth CBF and parametric optimization theory through directional derivatives for the first time, so as to solve PVM problems more conveniently. In detail, inspired by Chebyshev ball approach, a parametric linear program (PLP) based nonsmooth barrier function candidate is established for PVM, and then, sufficient conditions for it to be a nonsmooth CBF are proposed, based on which a quadratic program (QP) based safety filter with guaranteed feasibility is proposed to address PVM problems. Finally, a numerical simulation example is given to show the efficiency of the proposed safety filter. © 2025, CC BY.

关键词： Chebyshev filters

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control Aspects in Programming by Demonstation for Robotic Deep- Micro- Hole Drilling 32

Control Aspects in Programming by Demonstation for Robotic D...

引用

32nd Mediterranean Conference on control and Automation, MED 2024

作者： Maric, Bruno Petric, Frano Orsag, Matko University of Zagreb LARICS Laboratory for Robotics and Intelligent Control Systems Faculty of Electrical Engineering and Computing Zagreb10000 Croatia

ISBN: (纸本)9798350395440

This paper explores control aspects in a collab-orative robotic system designed to replicate human operators' drilling skills in deep- micro- hole tasks, focusing on the glass-container mould industry. To replicate human performance, we develop a single-DOF Impedance-based drill controller for a standard industrial position-controlled robot, enhancing safe and smooth interactions between the drill bit and the mould. To address high feed rates observed in worker demonstrations and prevent bit breaks, we focus on minimizing non-axial motion during drilling on an off-the-shelf available industrial manipulator KUKA KR 10. This involves analyzing the impact of joint dynamics on drill motion and designing a control system for the robot's low-level control to achieve axial drill motion. We show that the proposed joint control system that takes into account relationship between joint and tool dynamics outperforms available robot low-level control in minimizing non-axial motion, leading to the robot being able to outperform the human in deep- micro- hole drilling. © 2024 IEEE.

关键词： Molds

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Autonomous docking and energy sharing between two types of robotic agents

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IFAC-PapersOnLine 2018年第29期51卷 406-411页

作者： Babi, Anja Mandi, Filip Vasiljevi, Goran Mikovi, Nikola Faculty of Electrical Engineering and Computing LABUST Laboratory for Underwater Systems and Technologies University of Zagreb Unska 3 Zagreb Croatia Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Unska 3 Zagreb Croatia

In order to achieve long-term autonomy after deployment, a method of energy sharing within a heterogeneous swarm of marine robots was devised and implemented. This paper describes hardware and software solutions as well as guidance and control algorithms developed with the goal of allowing powerful energy-rich overactuated surface platforms to approach, dock, and wirelessly recharge less mobile sensor-rich agents upon request using visual servoing. The basic image processing algorithm uses data acquired by the Microsoft Kinect sensor alternating between RGB and infra-red camera modes, depending on lighting conditions. The full search and docking procedure developed for long-term operation is described. The results of a series of experiments done both in an indoor testbed and in realistic outdoor conditions are discussed and some goals for future work are given. © 2018

关键词： Autonomous agents

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A KNOWLEDGE-BASED APPROACH TO MODELING OF ROBOTIC ASSEMBLY CELLS

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ROBOTICA 1991年第1期9卷 31-42页

作者： KIM, DW LEE, BH KO, MS Robotics and Intelligent Systems Laboratory Department of Control and Instrumentation Engineering Seoul National University Seoul 151–742 (Korea)

In this paper, an approach to modelling of a robotic assembly cell is proposed and a method for managing the cell operation is described using a knowledge base. Since the modelling structure is based on the concept of the state variable, the relationships between states are described by the state transition map (STM). The knowledge-bases for state transition and assembly job information are obtained from the STM and the assembly job tree (AJT), respectively. Using the knowledge-base, the system structure is discussed in relation to both managing the cell operation and evaluating the performances. Finally, a simulation algorithm is presented with the simulation results to show the significance of the proposed modelling approach.

关键词： MODELING ASSEMBLY CELLS robotics KNOWLEDGE-BASE STATE TRANSITION

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Construction of Multilayer Porous Scaffold Based on Magnetically Guided Assembly of Microfiber

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Journal of systems Science & Complexity 2018年第3期31卷 581-595页

作者： LI Xingfu WANG Huaping SHI Qing SUN Tao HUANG Qiang FUKUDA Toshio Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing 100081 China Key Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing 100816 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 China

This paper proposes a novel method of magnetically guided assembly to construct multi- layer porous scaffold for three-dimensional cell culture by apply magnetic microfibers. Microfibers are composed of biocompatible and biodegradable alginate solution with homogeneous magnetic nanopar- ticles, which are continuously spun from a microfluidic device by precise pressure control of the syringe pump. Magnetic nanoparticles enable the control of magnetic field on microfibers. Meanwhile, mag- netized device combining with a round permanent magnet are utilized to guide the distribution of spouted microfibers. The device is composed by pure iron wire arrays and wax, which stimulates pow- erful magnetic flux density and magnetic field gradients for the capture and assembly of microfibers. Thus, magnetic microfibers are spun on desired places of the magnetized device by motion control of the micromanipulation robot, and precise locations are adjusted by magnetic force couple with the assist of glass micropipette. Afterwards, microfibers are spatially organized by periodic magnetic force and crossed layer-by-layer to form micro-pore structure with both length and width of 650μm. Finally, the authors construct a multilayer microfiber-based scaffold with high porosity to provide a satisfactory environment for long-term cell culture. The experimental results demonstrate the effectiveness of the proposed method.

关键词： Magnetically guided assembly magnetic microfiber magnetized device periodic magneticforce multilayer porous scaffold.

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Decentralized Energy Sharing Protocol using TÆMS Framework and Coalition-based Metaheuristic for Heterogeneous Robotic systems

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IFAC-PapersOnLine 2017年第1期50卷 5914-5919页

作者： Arbanas B. Boljuncic S. Petrovic T. Bogdan S. University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Croatia

In this paper we describe a decentralized protocol that is applied for scheduling and management of energy sharing in heterogeneous systems. Particular system we have in mind comprises of agents with different mobility, energy harvesting and energy sharing capabilities herein called aPads, aFish and aMussels. aPads are surface vehicles that harvest energy and are able to transmit it to both aFishes and aMussels. aFish are underwater vehicles that can transmit energy to aMussels or to other aFish, and receive energy from aPads. aMussels, that can either be attached to the sea-ground or float on the surface, can only receive energy, either from aFish or aPads. For such a system to be able to function for an extended period of time, a decentralized energy management protocol should be designed, whose purpose is to schedule and coordinate charging of agents over time. These decisions depend on the current battery levels of different agents, as well as their positions, and should be done in a decentralized manner. In this paper we apply an energy sharing protocol based on TÆMS framework, originally applied to planning and coordination in aerial-ground robotics systems for search and rescue missions. We refine the obtained plans using the coalition-based metaheuristic for vehicle routing problems. We show execution schedules achieved using the proposed protocol and highlight its advantages and flaws when applied to our underwater scenario. © 2017

关键词： decentralized systems distributed artificial intelligence Hierarchical decision making scheduling algorithms

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Trust Consensus Protocol for Heterogeneous Underwater Robotic systems

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IFAC-PapersOnLine 2016年第23期49卷 341-346页

作者： Mazdin, Petra Arbanas, Barbara Haus, Tomislav Bogdan, Stjepan Petrovic, Tamara Miskovic, Nikola University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Croatia University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Underwater Systems and Technologies Croatia

In this paper we analyze the application of a binary trust-consensus protocol in multi-agent systems with switching communication topology. Trust represents belief of one agent that the other one is capable of executing a specific task. The approach is motivated by an underwater robot system in which robots, called aMussels, are dispersed in the environment and measure environmental properties (for example sea-current) over a longer period of time, with sensors which are prone to failures. The goal is to apply the binary trust-consensus protocol to enable the system to autonomously detect failures of aMussels. Since direct communication between aMussels is energy consuming, a new type of moving robot, called aFish, is introduced that serves as a carrier of information. Since aFish have a limited communication range, communication topology is switching. Simulations are run first in Matlab for a homogeneous system, and then in a realistic simulation environment for the described scenario with heterogeneous agents. Results show that the protocol converges to the correct trust values and that the convergence time depends on the connectivity of the communication graph. © 2016

关键词： Multi agent systems MATLAB Robots Topology Communication graphs Communication topologies Direct communications Environmental property Heterogeneous multi agent systems Limited communication range Switching topology trust consensus

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Online Estimation Of Risk in AUV Course Keeping Problem

Online Estimation Of Risk in AUV Course Keeping Problem

引用

2023 International Conference on Ocean Studies, ICOS 2023

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

ISBN: (纸本)9798350382457

The article is devoted to the problem of assessing the risk of the presence of an autonomous underwater vehicle in a position limited by a given course angle at every moment of the system's operation. These risky situations arise in the tasks of navigation, docking, tracking objects, receiving and transmitting data in the underwater environment. To perform risk assessments, the most probable trajectories of movement to the threshold values of phase states are used. The most probable trajectories are calculated by solving the minimization problems of the so-called quasipotentials with differential coupling in the form of linear differential equations describing an object and external disturbances acting on it. As a result, we have information about the trajectories of movement, time and probability of events when the object moves along the trajectory. Comparing the current state of the object with known trajectories at each moment of the system operation, an assessment is made of how close the object is to the threshold values. The evaluation results are presented in the form of numerical simulation, which are then aggregated and shown in the form of quality metrics of the forecast of the time remaining until the threshold is crossed. The forecast cannot be carried out for a sufficiently longer amount of time, since the nature of the risk situation already determines the functioning of the object in the danger zone. The estimation of the boundary of this prediction is also shown by simulation using the Monte Carlo method. © 2023 IEEE.

关键词： Trajectories

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