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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Carlos Sampedro Hriday Bavle Alejandro Rodríguez-Ramos Adrian Carrio Ramon A. Suárez Fernández Jose Luis Sanchez-Lopez Pascual Campoy Computer Vision and Aerial Robotics (CVAR) Group Centre for Automation and Robotics (UPM-CSIC) Madrid Spain

ISBN: (纸本)9781509044962

In this paper, a fully-autonomous quadrotor aerial robot for solving the different missions proposed in the 2016 International Micro Air Vehicle (IMAV) Indoor Competition is presented. The missions proposed in the IMAV 2016 competition involve the execution of high-level missions such as entering and exiting a building, exploring an unknown indoor environment, recognizing and interacting with objects, landing autonomously on a moving platform, etc. For solving the aforementioned missions, a fully-autonomous quadrotor aerial robot has been designed, based on a complete hardware configuration and a versatile software architecture, which allows the aerial robot to complete all the missions in a fully autonomous and consecutive manner. A thorough evaluation of the proposed system has been carried out in both simulated flights, using the Gazebo simulator in combination with PX4 Software-In-The-Loop, and real flights, demonstrating the appropriate capabilities of the proposed system for performing high-level missions and its flexibility for being adapted to a wide variety of applications.

关键词： Sensors Unmanned aerial vehicles Cameras Feature extraction Robots Navigation Planning

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Natural user interfaces for human-drone multi-modal interaction

Natural user interfaces for human-drone multi-modal interact...

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2016 International Conference on Unmanned Aircraft Systems, ICUAS 2016

作者： Fernandez, Ramon A. Suarez Sanchez-Lopez, Jose Luis Sampedro, Carlos Bavle, Hriday Molina, Martin Campoy, Pascual Computer Vision Group Centre for Automation and Robotics CSIC-UPM Spain Spain

ISBN: (纸本)9781467393331

Personal drones are becoming part of every day life. To fully integrate them into society, it is crucial to design safe and intuitive ways to interact with these aerial systems. The recent advances on User-Centered Design (UCD) applied to Natural User Interfaces (NUIs) intend to make use of human innate features, such as speech, gestures and vision to interact with technology in the way humans would with one another. In this paper, a Graphical User Interface (GUI) and several NUI methods are studied and implemented, along with computer vision techniques, in a single software framework for aerial robotics called Aerostack which allows for intuitive and natural human-quadrotor interaction in indoor GPS-denied environments. These strategies include speech, body position, hand gesture and visual marker interactions used to directly command tasks to the drone. The NUIs presented are based on devices like the Leap Motion Controller, microphones and small size monocular on-board cameras which are unnoticeable to the user. Thanks to this UCD perspective, the users can choose the most intuitive and effective type of interaction for their application. Additionally, the strategies proposed allow for multi-modal interaction between multiple users and the drone by being able to integrate several of these interfaces in one single application as is shown in various real flight experiments performed with non-expert users. © 2016 IEEE.

关键词： Drones

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Understanding metric-related pitfalls in image analysis validation

arXiv

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arXiv 2023年

作者： Reinke, Annika Tizabi, Minu D. Baumgartner, Michael Eisenmann, Matthias Heckmann-Nötzel, Doreen Kavur, A. Emre Rädsch, Tim Sudre, Carole H. Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Benis, Arriel Blaschko, Matthew B. Buettner, Florian Cardoso, M. Jorge Cheplygina, Veronika Chen, Jianxu Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hashimoto, Daniel A. Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kenngott, Hannes Kleesiek, Jens Kofler, Florian Kooi, Thijs Kopp-Schneider, Annette Kozubek, Michal Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Petersen, Jens Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Riegler, Michael A. Rieke, Nicola Saez-Rodriguez, Julio Sánchez, Clara I. Shetty, Shravya Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. van Calster, Ben Varoquaux, Gaël Yaniv, Ziv R. Jäger, Paul F. Maier-Hein, Lena Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Intelligent Medical Systems Germany NCT Heidelberg A Partnership Between DKFZ University Medical Center Heidelberg Germany Heidelberg Division of Medical Image Computing Germany Heidelberg Division of Intelligent Medical Systems Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montreal Canada Division of Computational Pathology Dept of Pathology & Laboratory Medicine Indiana University School of Medicine IU Health Information and Translational Sciences Building Indianapolis United States University of Pennsylvania Richards Medical Research Laboratories FL7 PhiladelphiaPA United States Department of Digital Medical Technologies Holon Institute of Technology Holon Israel European Federation for Medical Informatics Le Mont-sur-Lausanne Switzerland Center for Processing Speech and Images Department of Electrical Engineering KU Leuven Leuven Belgium partner site Frankfurt/Mainz a partnership between DKFZ and UCT Frankfurt Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany and Frankfurt Cancer Insititute Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for Statistics in Medicine University of Oxford Oxford United Kingdom Center for Biomedical In

Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately. While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. While focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation. © 2023, CC BY.

关键词： computer vision

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AEROSTACK: An architecture and open-source software framework for aerial robotics

AEROSTACK: An architecture and open-source software framewor...

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2016 International Conference on Unmanned Aircraft Systems, ICUAS 2016

作者： Sanchez-Lopez, Jose Luis Fernandez, Ramon A. Suarez Bavle, Hriday Sampedro, Carlos Molina, Martin Pestana, Jesus Campoy, Pascual Computer Vision Group Centre for Automation and Robotics CSIC UPM Spain Department of Artificial Intelligence Technical University of Madrid UPM Spain

ISBN: (纸本)9781467393331

To simplify the usage of the Unmanned Aerial Systems (UAS), extending their use to a great number of applications, fully autonomous operation is needed. There are many open-source architecture frameworks for UAS that claim the autonomous operation of UAS, but they still have two main open issues: (1) level of autonomy, being in most of the cases limited and (2) versatility, being most of them designed specifically for some applications or aerial platforms. As a response to these needs and issues, this paper presents Aerostack, a system architecture and open-source multi-purpose software framework for autonomous multi-UAS operation. To provide higher degrees of autonomy, Aerostack's system architecture integrates state of the art concepts of intelligent, cognitive and social robotics, based on five layers: reactive, executive, deliberative, reflective, and social. To be a highly versatile practical solution, Aerostack's open-source software framework includes the main components to execute the architecture for fully autonomous missions of swarms of UAS;a collection of ready-to-use and flight proven modular components that can be reused by the users and developers;and compatibility with five well known aerial platforms, as well as a high number of sensors. Aerostack has been validated during three years by its successful use on many research projects, international competitions and exhibitions. To corroborate this fact, this paper also presents Aerostack carrying out a fictional fully autonomous indoors search and rescue mission. © 2016 IEEE.

关键词： Open source software

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AEROSTACK: An architecture and open-source software framework for aerial robotics

AEROSTACK: An architecture and open-source software framewor...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Jose Luis Sanchez-Lopez Ramón A. Suárez Fernández Hriday Bavle Carlos Sampedro Martin Molina Jesus Pestana Pascual Campoy Consejo Superior de Investigaciones Cientificas Madrid Madrid ES Computer Vision Group Centre for Automation and Robotics CSIC - UPM Madrid Madrid ES Computer Vision Group Centre for Automation and Robotics CSIC - UPM Spain Technical University of Madrid (UPM) Spain Computer Vision Group CSIC-UPM Spain

ISBN: (纸本)9781467393355

To simplify the usage of the Unmanned Aerial Systems (UAS), extending their use to a great number of applications, fully autonomous operation is needed. There are many open-source architecture frameworks for UAS that claim the autonomous operation of UAS, but they still have two main open issues: (1) level of autonomy, being in most of the cases limited and (2) versatility, being most of them designed specifically for some applications or aerial platforms. As a response to these needs and issues, this paper presents Aerostack, a system architecture and open-source multi-purpose software framework for autonomous multi-UAS operation. To provide higher degrees of autonomy, Aerostack's system architecture integrates state of the art concepts of intelligent, cognitive and social robotics, based on five layers: reactive, executive, deliberative, reflective, and social. To be a highly versatile practical solution, Aerostack's open-source software framework includes the main components to execute the architecture for fully autonomous missions of swarms of UAS; a collection of ready-to-use and flight proven modular components that can be reused by the users and developers; and compatibility with five well known aerial platforms, as well as a high number of sensors. Aerostack has been validated during three years by its successful use on many research projects, international competitions and exhibitions. To corroborate this fact, this paper also presents Aerostack carrying out a fictional fully autonomous indoors search and rescue mission.

关键词： computer architecture Feature extraction Software Hardware Robot sensing systems

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A flexible and dynamic mission planning architecture for UAV swarm coordination

A flexible and dynamic mission planning architecture for UAV...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Carlos Sampedro Hriday Bavle Jose Luis Sanchez-Lopez Ramon A. Suárez Fernández Alejandro Rodríguez-Ramos Martin Molina Pascual Campoy Computer Vision Group Center for Automation and Robotics (UPM-CSIC) Madrid Spain Department of Artificial Intelligence Technical University of Madrid (UPM) Spain

ISBN: (纸本)9781467393355

In this paper a scalable and flexible Architecture for real-time mission planning and dynamic agent-to-task assignment for a swarm of Unmanned Aerial Vehicles (UAV) is presented. The proposed mission planning architecture consists of a Global Mission Planner (GMP) which is responsible of assigning and monitoring different high-level missions through an Agent Mission Planner (AMP), which is in charge of providing and monitoring each task of the mission to each UAV in the swarm. The objective of the proposed architecture is to carry out high-level missions such as autonomous multi-agent exploration, automatic target detection and recognition, search and rescue, and other different missions with the ability of dynamically re-adapt the mission in real-time. The proposed architecture has been evaluated in simulation and real indoor flights demonstrating its robustness in different scenarios and its flexibility for real-time mission re-planning and dynamic agent-to-task assignment.

关键词： computer architecture Planning Robot kinematics Monitoring Real-time systems Trajectory

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Real-time monocular obstacle avoidance using underwater dark channel prior

Real-time monocular obstacle avoidance using underwater dark...

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2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016

作者： Drews, Paulo Hernández, Emili Elfes, Alberto Nascimento, Erickson R. Campos, Mario Autonomous Systems Laboratory Data61-CSIRO Brisbane Australia Computer Vision and Robotics Laboratory Dep. de Ciência da Computação Univ. Federal de Minas Gerais - UFMG Belo Horizonte Brazil NAUTEC Intelligent Robotics and Automation Group Univ. Federal do Rio Grande - FURG Rio Grande Brazil

ISBN: (纸本)9781509037629

In this paper we propose a new vision-based obstacle avoidance strategy using the Underwater Dark Channel Prior (UDCP) that can be applied to any Unmanned Underwater Vehicle (UUV) equipped with a simple monocular camera and minimal on-board processing capabilities. For each incoming image, our method first computes a relative depth map to estimate the obstacles nearby. Then, the map is segmented and the most promising Region of Interest (RoI) is identified. Finally, an escape direction is computed within the RoI and a control action is performed accordingly to avoid the obstacles. We tested our approach on a video sequence in a natural environment and compared it against a stateofthe-art method showing better performance, specially in light changing conditions. We also provide online results on a low-cost Remotely Operated Vehicle (ROV) in a controlled environment. © 2016 IEEE.

关键词： Remotely operated vehicles

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Model predictive position/force control of an anthropomorphic robotic arm

Model predictive position/force control of an anthropomorphi...

引用

2015 IEEE International Conference on Industrial Technology, ICIT 2015

作者： De La Casa Cardenas, J. Garcia, A. Sanchez Martinez, S. Satorres Garcia, J. Gamez Ortega, J. Gomez Group of Robotics Automation and Computer Vision University of Jaén Germany

ISBN: (纸本)9781479978007

When a robotic manipulator executes a task in restricted and unknown environments, it is necessary to implement a position/force control in free space and constrained space. In classic controllers, position/force control may be carried out by means a controller switching, once the contact point has been reached. In this paper, a new position/force predictive controller for an anthropomorphic robotic arm is proposed. This work proposes an unique control law for controlling both variables (position or force). In a model predictive framework, where several goals have to be reached, it is known that cost function includes several parameters (weights) whose modification allows to prioritize goals to achieve. This fact has been taken into account to set up the controller. The proposed control law is validated by experiments involving a 7-dof anthropomorphic robotic arm executing a trajectory tracking task in a restricted environment. As experimental results show, it is possible to control position and force by adjusting controller weights. © 2015 IEEE.

关键词： Robotic arms

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Natural User Interfaces for Human-Drone Multi-Modal Interaction

Natural User Interfaces for Human-Drone Multi-Modal Interact...

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International Conference on Unmanned Aircraft Systems

作者： Ramón A. Suárez Fernández Jose Luis Sanchez-Lopez Carlos Sampedro Hriday Bavle Martin Molina Pascual Campoy Computer Vision Group Centre for Automation and Robotics CSIC-UPM (Spain)

ISBN: (纸本)9781467393355

关键词： UCD Natural User

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A real-time supervised learning approach for sky segmentation onboard unmanned aerial vehicles

A real-time supervised learning approach for sky segmentatio...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Adrian Carrio Carlos Sampedro Changhong Fu Jean-François Collumeau Pascual Campoy Computer Vision Group Center for Automation and Robotics (UPM-CSIC) Madrid Spain School of Mechanical and Aerospace Engineering and ST Engineering-NTU Corp Laboratory Nanyang Technological University Singapore

vision-based sky segmentation and horizon line detection can be extremely useful to perform important tasks onboard Unmanned Aerial Vehicles (UAVs), such as pose estimation and collision avoidance. Most of the existing vision-based solutions use traditional image processing methods to identify the horizon line. This results in good overall accuracy and fast computation times. However, difficult environmental conditions such as a foggy or cloudy skies hinder correct sky segmentation. This paper proposes a solution for sky segmentation in RGB images using a supervised Machine Learning approach by first splitting the image into fixed-size patches, extracting and classifying color descriptors for each patch and performing a final post-processing stage to improve segmentation quality. A method for automatic horizon line detection is also proposed. The performance of our approach was evaluated on flight images captured onboard UAVs, achieving performance accuracies above 93% at real-time frame rates.

关键词： Image color analysis Image segmentation Aircraft Image edge detection Histograms Real-time systems Unmanned aerial vehicles

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