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A Multi-User Multi-Robot Collaboration through Augmented Reality

A Multi-User Multi-Robot Collaboration through Augmented Rea...

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

作者： João G. Martins Gabriel M. Costa Marcelo R. Petry Paulo Costa António Paulo Moreira CRIIS – Centre for 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 (FEUP) Porto Portugal

ISBN: (数字)9798350352344

ISBN: (纸本)9798350352351

Current industrial environments have multiple robots working alongside humans, thus providing an operator the ability to perceive the robot’s workspace correctly and to anticipate its intentions and movements through the visualization of the robot’s digital twin is of utmost importance for safe and productive human-robot collaboration scenarios. Much has been studied regarding single human-single robot collaborative scenarios, but few address multi-user multi-robot scenarios. To this end, this paper presents a multi-robot multi-operator architecture, where the users’ awareness is enhanced through an augmented reality head-mounted display. A multi-robot, multi-user collaborative scenario is presented in a laboratory environment with two industrial robots. Besides being able to interact with both robots in the system, each user becomes more aware of the robot’s workspace and its pre-defined trajectories. Furthermore, it presents how fiducial markers can help to establish the relation between the different coordinate frames.

关键词： Visualization Service robots Robot kinematics Scalability Collaboration User interfaces Trajectory

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Sigma-Delta Modulation for Enhanced Underwater Optical Wireless Communication systems

Sigma-Delta Modulation for Enhanced Underwater Optical Wirel...

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International Conference on Transparent Optical Networks

作者： João H. Araújo Henrique J. Rocha Joana S. Tavares Henrique M. Salgado INESC TEC—Institute for Systems and Computer Engineering Technology and Science Porto Portugal Faculty of Engineering University of Porto Porto Portugal

This paper presents an experimental investigation of sigma-delta modulation (SDM) as a means of improving the performance of underwater optical communication systems. The study considers the impact of the key parameters of SDM, including oversampling ratio, the system’s signal-to-noise ratio, bandwidth, and optical link distance. The results of this study provide insights into the design and optimization of SDM-based underwater optical communication systems, paving the way for future research in this field. A fully digital solution, albeit operating at a lower bit rate than previously published OFDM counterparts, provides immunity against nonlinearities of the system and robustness to noise, which is relevant in harsh environments. Moreover, the proposed solution based on a first-order bandpass SDM architecture avoids the employment of a DAC at the receiver, simplifying its operation and reducing costs. An experimental investigation is carried out for the transmission of 16-QAM over SDM, and a transmission distance of 4.8 m over the underwater channel is achieved with a maximum transmission rate of 400 Mbit/s with an MER of 28 dB.

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The Role of Batteries in Maximizing Green Hydrogen Production with Power Flow Tracing

The Role of Batteries in Maximizing Green Hydrogen Productio...

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Workshop on Smart Grid and Renewable Energy (SGRE)

作者： Ekaterina Dudkina José Villar Ricardo Jorge Bessa Emanuele Crisostomi Department of Energy Systems Territory and Constructions Engineering (DESTEC) University of Pisa Pisa Italy Center for Power and Energy Systems (CPES) Institute for Systems and Computer Engineering of Porto (INESC TEC) Porto Portugal

Hydrogen is currently getting more and more attention in the European climate strategy as a promising enabling technology to decarbonize industry, transport sector and to provide a long-term, high-capacity energy storage solution. However, to truly contribute to the reduction of CO 2 emissions, hydrogen must be produced respecting a principle of additionality, to ensure that it is produced using renewable energy sources and that its production does not decrease the green energy supplied to other loads. This study tracks the share of renewables generation in the energy mix used to produce hydrogen by applying a power flow tracing technique integrated with an optimal power flow analysis. This method allows the minimization of the system operation costs, while maximizing the green hydrogen production and considering the additionality principle. The system cost function is also modified to include the sizing and allocation of conventional batteries in the grid, and assess their ability to further increase the share of green energy in hydrogen production.

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Integrating Multimodal Perception into Ground Mobile Robots

Integrating Multimodal Perception into Ground Mobile Robots

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

作者： Ricardo B. Sousa Héber Miguel Sobreira João G. Martins Paulo G. Costa Manuel F. Silva António Paulo Moreira Faculty of Engineering University of Porto (FEUP) Porto Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal ISEP Polytechnic of Porto Porto Portugal

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

Multimodal perception systems enhance the robustness and adaptability of autonomous mobile robots by integrating heterogeneous sensor modalities, improving long-term localisation and mapping in dynamic environments and human-robot interaction. Current mobile platforms often focus on specific sensor configurations and prioritise cost-effectiveness, possibly limiting the flexibility of the user to extend the original robots further. This paper presents a methodology to integrate multimodal perception into a ground mobile platform, incorporating wheel odometry, 2D laser scanners, 3D Light Detection and Ranging (LiDAR), and RGBD cameras. The methodology describes the electronics design to power devices, firmware, computation and networking architecture aspects, and mechanical mounting for the sensory system based on 3D printing, laser cutting, and bending metal sheet processes. Experiments demonstrate the usage of the revised platform in 2D and 3D localisation and mapping and pallet pocket estimation applications. All the documentation and designs are accessible in a public repository.

关键词： Laser radar Robot vision systems Wheels Three-dimensional printing Cameras Distance measurement Robustness Mobile robots Laser beam cutting Autonomous robots

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Characterization of an hollow core PCF for endoscopy applications: A proof concept

Characterization of an hollow core PCF for endoscopy applica...

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2021 Telecoms Conference, ConfTELE 2021

作者： Marques, Joao Novais, Susana Silva, Susana Frazao, Orlando Faculty of Sciences University of Porto Inesc Tec Department of Physics and Astronomy Porto Portugal Inesc Tec Institute for Systems and Computer Engineering Technology and Science Porto Portugal

ISBN: (纸本)9781665415880

Two distinct optical fibers for endoscope-based configurations are demonstrated and studied in this work. The fibers used for the experiment consist of: a conventional singlemode fiber (SMF 28e) and a hollow core photonic crystal fiber (HC-PCF) based on silica. Two studies that allowed the characterization of these fibers, according to their optical output power and when subjected to curvature, were carried out. The intensity power profile was also analysed in relation to the propagation distance, transversal displacement and incidence angle. After this study it can be concluded that the most suitable solution for the endoscope is the HC-PCF fiber working as a transmission probe. For the proof of concept of the fiber-based endoscope, a cleaved multimode fiber (MMF) tip was used as a reception probe and its reflection efficiency was also analysed. © 2021 IEEE.

关键词： Endoscopy

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GDBN, A Customer-centric Digital Platform to Support the Value Chain of Flexibility Provision

GDBN, A Customer-centric Digital Platform to Support the Val...

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International Conference on European Electricity Market, EEM

作者： Fábio Coelho Luís Rodrigues João Mello José Villar Ricardo Bessa INESC TEC - Institute for Systems and Computer Engineering Technology and Science Universidade do Minho Faculdade de Engenharia da Universidade do Porto Portugal

ISBN: (数字)9798350381740

ISBN: (纸本)9798350381757

This paper proposes an original framework for a flexibility-centric value chain and describes the pre-specification of the Grid Data and Business Network (GDBN), a digital platform to provide support to the flexibility value chain activities. First, it outlines the structure of the value chain with the most important tasks and actors in each activity. Next, it describes the GDBN concept, including stakeholders’ engagement and conceptual architecture. It presents the main GDBN services to support the flexibility value chain, including, matching consumers and assets and service providers, assets installation and operationalization to provide flexibility, services for energy communities and services, for consumers, aggregators, and distribution systems operators, to participate in flexibility markets. At last, it details the workflow and life cycle management of this platform and discusses candidate business models that could support its implementation in real-life scenarios.

关键词： Procurement Renewable energy sources Europe Focusing Regulation Stakeholders Task analysis

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Performing Aerobatic Maneuver with Imitation Learning 23rd

Performing Aerobatic Maneuver with Imitation Learning

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23rd International Conference on Computational Science, ICCS 2023

作者： Freitas, Henrique Camacho, Rui Silva, Daniel Castro Department of Informatics Engineering Faculty of Engineering University of Porto Rua Dr. Roberto Frias s/n. Porto4200-465 Portugal LIAAD/INESC TEC - Artificial Intelligence and Decision Support Laboratory/Institute for Systems and Computer Engineering Technology and Science Porto Portugal LIACC - Artificial Intelligence and Computer Science Laboratory Porto Portugal

ISBN: (纸本)9783031359941

The work reported in this article addresses the challenge of building models for non-trivial aerobatic aircraft maneuvers in an automated fashion. It is built using a Behavioural Cloning approach where human pilots provide a set of example maneuvers used by a Machine Learning algorithm to induce a control model for each maneuver. The best examples for each maneuver were selected using a set of objective evaluation metrics. Using those example sets, robust models were induced that could replicate (and in some cases outperform) the human pilots that provided the examples (the clean-up effect). Complete complex maneuvers were performed using a meta-controller capable of sequencing the basic ones learned by imitation. This endeavor was rewarded by the results that show several Machine Learning models capable of performing highly complex aircraft maneuvers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cloning

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Review of Commercial Flexibility Products and Market Platforms

Review of Commercial Flexibility Products and Market Platfor...

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International Conference on European Electricity Market, EEM

作者： Luís Rodrigues Kamalanathan Ganesan Fábio Retorta Fábio Coelho João Mello José Villar Ricardo Bessa Technology and Science INESC TEC - Institute for Systems and Computer Engineering Faculdade de Engenharia da Universidade do Porto Universidade do Minho Portugal

ISBN: (数字)9798350381740

ISBN: (纸本)9798350381757

The European Union is pushing its members states to implement regulations that incentivize distribution system operators to procure flexibility to enhance grid operation and planning. Since flexibility should be obtained using market-based solutions, when possible, flexibility market platforms become essential tools to harness consumer-side flexibility, supporting its procurement, trading, dispatch, and settlement. These reasons have led to the appearance of multiple flexibility market platforms with different structure and functionalities. This work provides a comprehensive description of the main flexibility platforms operating in Europe and provides a concise review of the platform main characteristics and functionalities, including their user segment, flexibility trading procedures, settlement processes, and flexibility products supported.

关键词： Procurement technological innovation Reviews Terminology Europe Regulation Planning

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Classification of endoscopic capsule pathologies using Multiple Instance Learning methods 16

Classification of endoscopic capsule pathologies using Multi...

引用

16th International Conference on ENTERprise Information systems, CENTERIS 2024 - 12th International Conference on Project MANagement, ProjMAN 2024 - 14th International Conference on Health and Social Care Information systems and technologies, HCist 2024

作者： Moreira, Vitor Machado, Eduardo Barbosa, Dalila Salgado, Marta Braz, Geraldo Cunha, António University of Trás-os-Montes e Alto Douro Vila Real5001-801 Portugal INESC TEC Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal Centro Hospitalar Universitário de Santo António Porto Portugal MA São Luís Brazil

This article presents an investigation into the classification of endoscopic capsule pathologies using Multiple Instance Learning (MIL) methods in conjunction with deep neural network architectures. The primary problem addressed in this study is the accurate and efficient detection of gastrointestinal pathologies, a significant challenge in medical diagnostics that can have a profound impact on patient outcomes. The use of endoscopic capsules is particularly important as they provide a minimally invasive method to capture comprehensive images of the gastrointestinal tract, facilitating early detection of conditions such as ulcers, polyps, bleeding, and Crohn's disease. Specifically, we explore three variants of MIL-Max, Mean, and Attention-for analysing sets of images captured by the endoscopic capsule. MIL was employed because it effectively handles scenarios where individual image instances are not explicitly labelled but are grouped in bags with known labels, making it suitable for the complex nature of endoscopic data. Furthermore, MIL has not yet been extensively applied in this modality, highlighting the innovative aspect of our approach. In addition, we evaluated the performance of three convolutional neural network architectures-VGG16, ResNet50, and DenseNet121-in the classification task. The results indicate that the combination of MIL methods and deep neural network architectures offers a promising approach to the detection and classification of gastrointestinal pathologies, with significant improvements in diagnostic accuracy and efficiency. © 2025 The Author(s).

关键词： Endoscopy

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Deep Reinforcement Learning Framework for UAV Indoor Navigation

Deep Reinforcement Learning Framework for UAV Indoor Navigat...

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Iberian Robotics Conference (ROBOT)

作者： João J. Martins Alexandre Amaral André Dias INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal FEUP - Faculdade de Engenharia da Universidade do Porto Portugal

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

Unmanned Aerial Vehicle (UAV) applications, particularly for indoor tasks such as inventory management, infrastructure inspection, and emergency response, are becoming increasingly complex with dynamic environments and their different elements. During operation, the vehicle's response depends on various decisions regarding its surroundings and the task goal. Reinforcement Learning techniques can solve this decision problem by helping build more reactive, adaptive, and efficient navigation operations. This paper presents a framework to simulate the navigation of a UAV in an operational environment, training and testing it with reinforcement learning models for further deployment in the real drone. With the support of the 3D simulator Gazebo and the framework Robot Operating System (ROS), we developed a training environment conceivably simple and fast or more complex and dynamic, explicit as the real-world scenario. The multi-environment simulation runs in parallel with the Deep Reinforcement Learning (DRL) algorithm to provide feedback for the training. TD3, DDPG, PPO, and PPO+LSTM were trained to validate the framework training, testing, and deployment in an indoor scenario.

关键词： Training Three-dimensional displays Operating systems Inventory management Inspection Autonomous aerial vehicles Deep reinforcement learning Vehicle dynamics Robots Testing

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