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2020 Advances in science and Engineering Technology International Conferences, ASET 2020

作者： D'Souza, Joanita Kaur, Maninder Jeet Mohamad, Hassan Anwar Maheshwari, Piyush Amity University Dubai Department of Computer Science Engineering Dubai United Arab Emirates Institute of Robotics and Intelligent Systems Toronto Canada

ISBN: (纸本)9781728146409

The aim of this paper is to evaluate the Transmission control protocol (TCP) delay performance of IEEE802.11 WLANs using Wireshark which is a network performance monitoring tool. It also shows a detailed study of sniffing tools, logging tools, pre filtering and post sniffing. This paper also provides a way to find the maximum TCP delays over a time period and to plot a graph using Microsoft excel in order to perform further analysis. The study was carried out in a real time WLAN environment. The output that is obtained shows the maximum delay over time along with certain filters that have been applied. This is only possible for the active nodes present in the network. © 2020 IEEE.

关键词： Transmission control protocol

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Parallel Optimization with Hard Safety Constraints for Cooperative Planning of Connected Autonomous Vehicles

Parallel Optimization with Hard Safety Constraints for Coope...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Zhenmin Huang Haichao Liu Shaojie Shen Jun Ma Robotics and Autonomous Systems Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Division of Emerging Interdisciplinary Areas The Hong Kong University of Science and Technology Hong Kong SAR China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong SAR China HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute Shenzhen China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

The development of connected autonomous vehicles (CAVs) facilitates the enhancement of traffic efficiency in complicated scenarios. Difficulties remain unsolved in developing an effective and efficient coordination strategy for CAVs. In this paper, we formulate the cooperative autonomous driving task of CAVs as an optimal control problem with safety conditions enforced as hard constraints, and propose a computationally-efficient parallel optimization framework to generate strategies for CAVs with the travel efficiency improved and the hard safety constraints satisfied. Specifically, all constraints involved are addressed appropriately with convex approximation, such that the convexity property of the reformulated optimization problem is exhibited. Then, a parallel optimization algorithm is presented to solve the reformulated optimization problem, with an embodied iterative nearest neighbor search strategy to determine the optimal passing sequence. It is noteworthy that the travel efficiency is enhanced and the computation burden is considerably alleviated with the proposed innovation development. We also examine the proposed method in CARLA simulator and perform thorough comparisons to demonstrate the effectiveness and efficiency of the proposed approach.

关键词： Technological innovation Optimal control Safety Computational efficiency Planning Vehicle dynamics Task analysis

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Integrated Optimization of Charging Infrastructure, Renewable Energy and Battery Electric Bus Scheduling Subject to Power Distribution Network Constraints

SSRN

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SSRN 2024年

作者： Najafi, Arsalan Gao, Kun Parishwad, Omkar Tsaousoglou, Georgios Jin, Sheng Yi, Wen Department of Architecture and Civil Engineering Chalmers University of Technology GothenburgSE-412 96 Sweden Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Institute of Intelligent Transportation Systems College of Civil Engineering and Architecture Zhejiang University Hangzhou310058 China Department of Building and Real Estate The Hong Kong Polytechnic University Hung Hom Hong Kong

The adoption of Battery Electric Buses (BEBs) in electric public transit systems presents a significant opportunity for advancing sustainable transportation. However, it also poses challenges to the coupled electric transport and energy systems, particularly concerning the safety and efficiency of Power Distribution Networks (PDN). This study introduces a comprehensive BEB-PDN framework designed for the joint optimization of charging infrastructure, charging scheduling, and integration of renewable energy resources, with a specific focus on their impacts on PDN. The complexity of the proposed model is primarily due to its extensive decision variables and nonlinear constraints. To address this, a decomposition approach is employed, linearizing the problem and dividing it into master and subproblems for efficient resolution. A case study in Skövde, Sweden demonstrates that without renewable energy integration, high charging demands from BEBs can lead to PDN safety violations, such as significant voltage drops at certain nodes. The incorporation of renewable energy sources with battery energy storage in the BEB transit system is shown to enhance the PDN's stability and safety while catering to the system's spatiotemporal charging demands. This study offers an optimization framework for the integrated planning of charging infrastructure, BEB systems, and renewable energy, providing empirical insights into their potential benefits. © 2024, The Authors. All rights reserved.

关键词： Electric buses

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Automated Food Intake Monitoring System to Prevent Malnutrition Using the Tiago Robot Camera*

Automated Food Intake Monitoring System to Prevent Malnutrit...

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Data science and Engineering in Healthcare, Medicine and Biology, IEEE EMBS Special Topic Conference on

作者： Fotios S. Konstantakopoulos Daphni K. Plati Labrina A. Pliakou Francesco Scotto Di Luzio Nevio Luigi Tagliamonte Loredana Zollo Manolis Tsiknakis Dimitrios I. Fotiadis Unit of Medical Technology and Intelligent Information Systems Materials Science and Engineering Department University of Ioannina Biomedical Research Institute FORTH Ioannina GR 45110 Greece Research Unit of Advanced Robotics and Human-Centred Technologies Campus Bio-Medico University Rome Italy Institute of Computer Science FORTH Heraklion Crete GR 70013 Greece

The management of a daily diet is a significant concern among individuals in modern culture. The utilization of dietary assessment systems has significantly contributed to the efficient management of malnutrition and dietary habits over a period of time. In order to determine the nutritional value of the food that individuals consume, this study introduces a novel food monitoring system and its architecture. By creating a dataset of food images in a tray and using image processing, machine learning, and computer vision techniques, the nutrients and calories consumed by a patient are calculated. The proposed system achieves a 95.6% Intersection over Union score in the segmentation task, 92.3% top-1 accuracy in the classification task, and 4.6 g mean weight absolute error in the weight estimation *** Relevance: The proposed system has the ability to calculate the nutritional composition, encompassing calories, proteins, fats, and carbs, of food consumed by a patient, making it suitable for nutritional monitoring applications and healthcare systems that aim to monitor malnutrition in hospital patients.

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Learning-based Control for PMSM Using Distributed Gaussian Processes with Optimal Aggregation Strategy

Learning-based Control for PMSM Using Distributed Gaussian P...

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Annual Conference of Industrial Electronics Society

作者： Zhenxiao Yin Xiaobing Dai Zewen Yang Yang Shen Georges Hattab Hang Zhao Robotics and Autonomous Systems Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Chair of Information-oriented Control Technical University of Munich Munich Germany Center for Artificial Intelligence in Public Health Research (ZKI-PH) Robert Koch Institute Berlin Germany Department of Mathematics and Computer Science Freie Universität Berlin Berlin Germany Department of Electronic & Computer Engineering The Hong Kong University of Science and Technology Hong Kong China

The growing demand for accurate control in varying and unknown environments has sparked a corresponding increase in the requirements for power supply components, including permanent magnet synchronous motors (PMSMs). To infer the unknown part of the system, machine learning techniques are widely employed, especially Gaussian process regression (GPR) due to its flexibility of continuous system modeling and its guaranteed performance. For practical implementation, distributed GPR is adopted to alleviate the high computational complexity. However, the study of distributed GPR from a control perspective remains an open problem. In this paper, a control-aware optimal aggregation strategy of distributed GPR for PMSMs is proposed based on the Lyapunov stability theory. This strategy exclusively leverages the posterior mean, thereby obviating the need for computationally intensive calculations associated with posterior variance in alternative approaches. Moreover, the straightforward calculation process of our proposed strategy lends itself to seamless implementation in high-frequency PMSM control. The effectiveness of the proposed strategy is demonstrated in the simulations.

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The Smart Hospital: Data and AI Challenges

The Smart Hospital: Data and AI Challenges

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Data science and Engineering in Healthcare, Medicine and Biology, IEEE EMBS Special Topic Conference on

作者： Daphni K. Plati Fotios S. Konstantakopoulos Theofanis Kalatzis Dimitrios Manousos Thomas Kassiotis Francesco Scotto Di Luzio Nevio Luigi Tagliamonte Loredana Zollo Manolis Tsiknakis Dimitrios I. Fotiadis Materials Science and Engineering Department Unit of Medical Technology and Intelligent Information Systems University of Ioannina Biomedical Research Institute FORTH Ioannina GR 45110 Greece Institute of Computer Science FORTH Heraklion Crete GR 70013 Greece Research Unit of Advanced Robotics and Human-Centred Technologies Campus Bio-Medico University Rome Italy

Healthcare systems generally constitute a combination of healthcare facilities and providers that collaborate in order to offer a complete range of healthcare services. As the primary providers of healthcare, hospitals hold an essential place in the healthcare system. This study introduces three novel automated Artificial Intelligence (AI) systems by using the robotic platform of the TIAGo robot: (i) an image-based system that monitors the food consumption of the patients and provides information regarding their energy intake to prevent malnutrition; (ii) a rehabilitation system that monitors patients as they perform prescribed exercises to prevent loss of mobility, and (iii) a monitoring system for the correctness of the oxygen therapy in terms of the proper positioning of the oxygen mask to prevent hypoxia complications. A well-designed observational clinical study is planned to evaluate and validate the utility and effectiveness of the proposed AI systems in improving patient stay in the hospital. For the abovementioned systems, three novel datasets were *** Relevance: Through the implementation of AI systems, the proposed research intends to provide specialists with an extra tool to aid in the monitoring of hospitalized patients, thus helping to prepare the way for the Smart Hospital.

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Constructive barrier feedback for collision avoidance in leader-follower formation control

arXiv

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arXiv 2023年

作者： Tang, Zhiqi Cunha, Rita Hamel, Tarek Silvestre, Carlos Institute for Systems and Robotics Instituto Superior Técnico Universidade de Lisboa Portugal Division of Decision and Control Systems KTH Royal Institute of Technology Sweden I3S-CNRS Université Côte d'Azur Institut Universitaire de France France Department of Electrical and Computer Engineering The Faculty of Science and Technology The University of Macau China

This paper proposes a novel constructive barrier feedback for reactive collision avoidance between two agents. It incorporates this feature in a formation tracking control strategy for a group of 2nd-order dynamic robots defined in three-dimensional space. Using only relative measurements between neighboring agents, we propose an elegant decentralized controller as the sum of a nominal tracking controller and the constructive barrier feedback for leader-follower formations under a directed single-spanning tree graph topology. The key ingredient is the use of divergent flow as a dissipative term, which slows down the relative velocity in the direction of the neighboring robots without compromising the nominal controller's performance. Compared to traditional barrier function-based optimization controllers, the proposed constructive barrier feedback avoids feasibility issues and results in more computationally efficient control algorithms with systematic equilibrium analysis. Simulations are provided to validate the effectiveness of the proposed control method. © 2023, CC BY-NC-ND.

关键词： Collision avoidance

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Theory of Mind Abilities Predict Robot's Gaze Effects on Object Preference

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IEEE Transactions on Affective Computing 2025年

作者： Manzi, Federico Ishikawa, Mitsuhiko Dio, Cinzia Di Itakura, Shoji Kanda, Takayuki Ishiguro, Hiroshi Massaro, Davide Marchetti, Antonella Università Cattolica del Sacro Cuore Research Unit on Theory of Mind Department of Psychology Milan Italy Università Cattolica del Sacro Cuore Research Unit in Psychology and Robotics in the Lifespan Department of Psychology Milan Italy IRCCS Fondazione Don Carlo Gnocchi Milan Italy Hitotsubashi University Hitotsubashi Institute for Advanced Study Japan Ritsumeikan University Kyoto Japan Kyoto University Department of Computer Science Human-Robot Interaction Laboratory Kyoto Japan IRC'HIL Keihana Science City Advanced Telecommunications Research Institute International Kyoto Japan Osaka University Department of Intelligent Systems Toyonaka Japan

This study investigated the differences between human and robot gaze in influencing preference formation, and examined the role of Theory of Mind (ToM) abilities in this process. Human eye gaze is one of the most important sources of information for social interaction and research has demonstrated its effectiveness in influencing people's preference. With increasing technological development, we will interact with robots that can exhibit gaze behavior and influence people's preference. It is unclear whether there are any differences between humans and robots in this process. The present study aimed to analyze the role of the gaze of a robot and a human in influencing the ascription of a preference to the gazer and the participants' preference. Furthermore, we examined the role of ToM abilities in preference formation. The results showed that the gaze has a greater effect on the gazer preference compared to participants' preference regardless of the agent (human or robot). In addition, ToM abilities predict both gazer and individual preferences in the robot's condition only even though different socio-cognitive mechanisms are involved. The study suggests that adults are cognitively able to process the gaze of a robot similar to a human, recognizing the underlying mental state. However, only for the robot, different cognitive mechanisms are involved in the gazer (i.e., perspective taking) and participants' preference formation (i.e., advanced ToM). © 2010-2012 IEEE.

关键词： Social robots

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Multi-agent systems with memories under DoS attacks

Multi-agent systems with memories under DoS attacks

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International Conference on Control, Automation, robotics and Vision (ICARCV)

作者： Ricardo Almeida Ewa Girejko Luís Machado Agnieszka B. Malinowska Natália Martins Department of Mathematics Center for Research and Development in Mathematics and Applications University of Aveiro Portugal Faculty of Computer Science Bialystok University of Technology Białystok Poland Institute of Systems and Robotics - University of Coimbra Coimbra Portugal Department of Mathematics University of Trás-os-Montes e Alto Douro (UTAD) Vila Real Portugal

ISBN: (纸本)9781665476881

The paper is devoted to multi-agent systems with memories under denial-of-service (DoS) attacks. The memory is represented by the fractional derivative that appears in the dynamics of the considered systems. The problem that we aim to address is, under which conditions the system continues to be stable or is in consensus mode, despite DoS attacks. Solutions to these problems are proposed in the presented theorems. We strengthen the theoretical considerations with numerical simulations.

关键词： Linear systems Sufficient conditions Automation Denial-of-service attack Numerical simulation Stability analysis Robots

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Self-Healing Distributed Swarm Formation Control Using Image Moments

arXiv

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arXiv 2023年

作者： Liu, C. Lin Donato Ridgley, Israel L. Elwin, Matthew L. Rubenstein, Michael Freeman, Randy A. Lynch, Kevin M. Department of Mechanical Engineering Northwestern University EvanstonIL60208 United States Center for Robotics and Biosystems Northwestern University EvanstonIL60208 United States Department of Electrical & Computer Engineering Northwestern University EvanstonIL60208 United States Department of Computer Science Northwestern University EvanstonIL60208 United States Northwestern Institute on Complex Systems Northwestern University EvanstonIL60208 United States

Human-swarm interaction is facilitated by a low-dimensional encoding of the swarm formation, independent of the (possibly large) number of robots. We propose using image moments to encode two-dimensional formations of robots. Each robot knows its pose and the desired formation moments, and simultaneously estimates the current moments of the entire swarm while controlling its motion to better achieve the desired group moments. The estimator is a distributed optimization, requiring no centralized processing, and self-healing, meaning that the process is robust to initialization errors, packet drops, and robots being added to or removed from the swarm. Our experimental results with a swarm of 50 robots, suffering nearly 50% packet loss, show that distributed estimation and control of image moments effectively achieves desired swarm formations. © 2023, CC BY.

关键词： Multi agent systems

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