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16th International Conference on Social robotics, ICSR + AI 2024

作者： Kumar, Amit Jose, Jaison Jain, Archit Kulkarni, Siddharth Arya, Kavi Centre for Systems and Control Indian Institute of Technology Bombay Mumbai India Embedded Real-Time Systems / e-Yantra Lab Indian Institute of Technology Bombay Mumbai India Computer Science and Engineering Department Indian Institute of Technology Bombay Mumbai India

ISBN: (纸本)9789819635214

With recent advancements in industrial robots, educating students in new technologies and preparing them for the future is imperative. However, access to industrial robots for teaching poses challenges, such as the high cost of acquiring these robots, the safety of the operator and the robot, and complicated training material. This paper proposes two low-cost platforms built using open-source tools like Robot Operating System (ROS) and its latest version ROS 2 to help students learn and test algorithms on remotely connected industrial robots. Universal robotics (UR5) arm and a custom mobile rover were deployed in different life-size testbeds, a greenhouse, and a warehouse to create an Autonomous Agricultural Harvester System (AAHS) and an Autonomous Warehouse Management System (AWMS). These platforms were deployed for a period of 7 months and were tested for their efficacy with 1,433 and 1,312 students, respectively. The hardware used in AAHS and AWMS was controlled remotely for 160 and 355 hours, respectively, by students over a period of 3 months. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Costs

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Optimizing Very Large Scale ITS Applications with Fast Fitness Evaluation

Optimizing Very Large Scale ITS Applications with Fast Fitne...

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IEEE Conference on Wireless Communications and Networking

作者： Nagacharan Teja Tangirala Rouven Rischert Christoph Sommer Alois Knoll Chair of Robotics Artificial Intelligence and Real-time Systems Technical University of Munich Munich Germany Faculty of Computer Science TU Dresden Germany

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

As wireless communication technology advances, the complexity of Vehicular Ad-hoc Network (VANET) simulations increases. This, however, is at odds with the need for increasingly large-scale Intelligent Transportation systems (ITS) scenarios to satisfy the demands of increasingly Artificial Intelligence (AI) based solutions. This paper aims to demonstrate that a high-performance simplified VANET simulator can be used for fitness evaluation without loss in solution quality. As an example, we implement a Roadside Unit (RSU) deployment approach based on a genetic algorithm. Disolv, a simplified VANET simulator, is used as a fitness evaluation tool. To validate the solution quality, the best solutions of a few select generations are evaluated with a fully-featured ns-3 driven VANET simulation. From the comparison of fitness values, it can be observed that the values from Disolv allow us to predict those obtained via ns-3. Further, the execution time analysis showcases the substantial performance gains of using a more abstract VANET simulator. A 4.6-hour analysis with Disolv contrasts approximately 300 days with ns-3 for the given scenario and settings. Finally, the potential applications and limitations of using a simplified VANET simulator are discussed.

关键词： Wireless communication Vehicular ad hoc networks Performance gain Complexity theory Artificial intelligence Optimization Intelligent transportation systems Genetic algorithms

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MESSI: Task Mapping and Scheduling Strategy for FPGA-based Heterogeneous real-time systems

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ACM Transactions on Design Automation of Electronic systems 2025年第3期30卷 1-29页

作者： Ahmadi-Pour, Sallar Saha, Sangeet Mcdonald-Maier, Klaus Drechsler, Rolf Institute of Computer Science University of Bremen Faculty 3 Mathematics and Computer Science Bremen Bremen Germany Robotics and Embedded Systems Research Group University of Essex School of Computer Science and Electronic Engineering Colchester United Kingdom Cyber-Physical Systems DFKI Rheinland-Pfalz Kaiserslautern Germany

Continuous demands for improved performance within constrained resource budgets are driving a move from homogeneous to heterogeneous processing platforms for the implementation of today's real-time (RT) embedded systems. The applications executing on such systems are typically represented as a Precedence Task Graph (PTG), where a node represents a task or algorithm for one functionality and edges represent the complex interactions between multiple functionalities. Due to RT constraints, the task graph needs to be executed within a specified deadline. Although some existing studies have looked into solving this challenge, comprehensive studies that combine the theoretical features of RT task-graph mapping and scheduling with practical runtime architectural characteristics have mostly been ignored to date. Hence, in this article, we consider the challenge of scheduling an RT application modeled as a single PTG, with the objective of minimizing the overall execution time under Hardware (HW) resource and deadline constraints for heterogeneous Central Processing Unit (CPU) + Field Programmable Gate Array (FPGA) architectures. First, we introduce an optimal solution using Integer Linear Programming (ILP). However, this ILP-based optimal solution suffers from computational complexity and does not scale well even for moderately large problem sizes. Hence, we additionally propose heuristic algorithms for task mapping and scheduling. The efficiency of the proposed scheme, named MESSI, has been evaluated through experiments using PTG on a practical CPU+FPGA system regarding current technology restrictions. Our experiments demonstrate that performance gains of 55.6% and area usage reductions of 46.3% are possible compared to full Software (SW) and HW execution, respectively. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Integer programming

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Design and Development of a Fixed-Wing Tail-Sitter Tethered VTOL Drone with Custom Autopilot and Robust Control Techniques 16th

Design and Development of a Fixed-Wing Tail-Sitter Tether...

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16th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2024

作者： Safaee, Ahmad Aguiar, A. Pedro Santos, Filipe Neves Moreira, Antonio Paulo SYSTEC-ARISE Research Center for Systems and Technologies Faculty of Engineering University of Porto Porto4200-465 Portugal INESC-TEC-Institute for Systems and Computer Engineering Technology and Science CRIIS-Centre for Robotics in Industry and Intelligent Systems Porto4200-465 Portugal INESC-TEC-Institute for Systems and Computer Engineering and DEEC/FEUP - Department of Electrical and Computer Engineering Faculty of Engineering of the University of Porto Porto4200-465 Portugal

ISBN: (纸本)9783031817236

The need for aerial platforms capable of sustained operation is critical in fields such as surveillance, agricultural monitoring, disaster response, and temporary telecommunication systems. Traditional unmanned aerial vehicles (UAVs) are hampered by limited battery capacity and inefficient energy utilization. This paper introduces an autonomous vertical flight drone tethered to a ground-based platform, which overcomes these limitations. The drone is designed to optimize its position and energy usage by harnessing wind currents, functioning similarly to a kite when conditions permit. This is enabled by a custom-designed autopilot system comprising both hardware and software tailored for this application. We detail the model identification process for three vertical take-off and landing (VTOL) drone systems, employing authentic data that measures lateral positional errors from the tether. Robust mixed sensitivity controllers are developed and implemented. The effectiveness of these controllers is validated through simulations showing their capability to handle uncertainties. Furthermore, the practical application and robust performance of the system are confirmed by a real-world case study, highlighting its potential in real operational environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： VTOL/STOL aircraft

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Retinal disorder diagnosis based on hybrid deep learning models

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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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Enhancing Mobile Robot Navigation: A Graph Decomposition Submodule for TEA*

Enhancing Mobile Robot Navigation: A Graph Decomposition Sub...

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IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Filipe Cardoso Diogo Miguel Matos Marina Brilhante Pedro Costat Héber Sobreira Carlos Silva CRIIS - Centre of Robotics in Industry and Intelligent Systems INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal Faculty of Engineering University of Porto Porto Portugal Flowbotic Mobile Systems SA Mangualde Portugal

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

Rising industrial complexity demands efficient mobile robots to drive automation and productivity. Effective navigation relies on perception, localization, mapping, path planning, and motion control, with path planning being key. The time Enhanced A * (TEA *) algorithm extends A * by adding time as a dimension to resolve temporal conflicts in multi-robot coordination. However, inconsistencies in edge lengths within the graph can hinder optimal path calculation. To address this, a Graph Decomposition submodule was developed to standardize edge lengths and temporal costs. Integrated into a ROS-based fleet coordination system, this approach significantly reduces execution time and improves coordination capacity.

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Parallel Path Planning for Multi-Robot Coordination

Parallel Path Planning for Multi-Robot Coordination

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IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Jorge Ribeiro Marina Brilhante Diogo Miguel Matos Carlos A. Silva Héber Sobreira Pedro Costa CRIIS - Centre of Robotics in Industry and Intelligent Systems INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal Faculty of Engineering University of Porto Porto Portugal Flowbotic Mobile Systems S.A Viseu Portugal

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

Multi-robot coordination aims to synchronize robots for optimized, collision-free paths in shared environments, addressing task allocation, collision avoidance, and path planning challenges. The time Enhanced A* (TEA*) algorithm addresses multi-robot pathfinding offering a centralized and sequential approach. However, its sequential nature can lead to order-dependent variability in solutions. This study enhances TEA* through multi-threading, using thread pooling and parallelization techniques via OpenMP, and a sensitivity analysis enabling parallel exploration of robot-solving orders to improve robustness and the likelihood of finding efficient, feasible paths in complex environments. The results show that this approach improved coordination efficiency, reducing replanning needs and simulation time. Additionally, the sensitivity analysis assesses TEA*'s scalability across various graph sizes and number of robots, providing insights into how these factors influence the efficiency and performance of the algorithm.

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APPLICATIONS OF FUZZY-LOGIC CONTROL IN AUTONOMOUS ROBOT systems

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INTERNATIONAL JOURNAL OF systems science 1993年第10期24卷 1885-1904页

作者： ZHANG, JW Institute for Real-Time Computer Systems and Robotics Department of Computer Science University of Karlsruhe Karlsruhe Germany

The development of autonomous robots involves the imitation of human decision-making abilities with the aid of diverse sensor information. Fuzzy logic, which is based on fuzzy modelling and approximate reasoning, can be applied in different levels of control tasks. We first present the research results of applying fuzzy logic control in the motion execution of mobile systems and sensor-guided fine-motion of a manipulator. To realize real-time 'reactive' control, suitable hardware which supports the acceleration of fuzzy inference should be developed. The design and development of a VME-bus compatible fuzzy co-processor is also described.

关键词： Fuzzy inference

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Model-based process redesign

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JOURNAL OF INTELLIGENT MANUFACTURING 1997年第5期8卷 345-356页

作者： Janusz, B Institute for Real-Time Computer Systems and Robotics Department of Computer Science University of Karlsruhe Karlsruhe Germany

A method is presented for the model-based redesign of enterprises. It consists of two main steps, the initialization step and the optimization step. During the initialization step, the processes are modelled and analysed. During the optimization step, the optimal configuration is found for the possible modifications of the processes. Emphasis is placed on the process analysis. The proposed approach is based on activity chains which describe the set of activities needed for the achievement of a given gear, and their execution order necessary to guarantee a low processing time. An algorithm is presented for filtering such activity chains from an enterprise model. It is based on graph theory and corresponds to the solution of an optimization problem, whereby the sum of weights of ail edges belonging to the solution graph should be maximized under some given constraints. Because of the high complexity of the problem, some complexity-reducing measures are presented, measures that arise from the earlier problem analysis.

关键词： process redesign process analysis activity chain graph theory

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AN INTEGRATED APPROACH TO SOFTWARE systems PLANNING AND SELECTION BASED ON CIMOSA MODELS

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CONTROL ENGINEERING PRACTICE 1995年第1期3卷 97-103页

作者： NAEGER, G REMBOLD, U Department of Computer Science Institute for Real-Time Computer Systems and Robotics University of Karlsruhe 76128 Karlsruhe Germany

Strong international competition forces enterprises to reduce organizational overhead and cost. Today's industrial practices allow, in general, only the selection of whole planning and control systems for CIM (e.g., CAD systems, PP&C systems,...). These systems can be adapted only in a limited range to the user requirements. With the introduction of executable enterprise models to the industrial environment, it is expected that it will be possible to design tailored CIM systems built of standardized software modules which will lead to higher complexity of the planning process for software systems. Thus, today's planning and selection approaches will face more and more problems. In order to master the increasing complexity of the planning of software systems for enterprises, new planning methods and tools are required. An integrated approach to software system planning and selection based on CIMOSA enterprise models was developed. The underlying idea of the approach is the conversion of the planning problem into an equivalent constraint satisfaction problem. The conversion process can be accomplished fully automatically.

关键词： ENTERPRISE MODELING CIMOSA RESOURCE SELECTION

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