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Iberian robotics Conference (ROBOT)

作者： Guillermo GP-Lenza Carmen DR.Pita-Romero Miguel Fernandez-Cortizas Pascual Campoy Computer Vision and Aerial Robotics group (CVAR) Centre for Automation and Robotics (CAR) Universidad Politécnica de Madrid (UPM) Madrid Spain

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

This paper presents a comprehensive methodology for implementing knowledge graphs in ROS 2 systems, aiming to enhance the efficiency and intelligence of autonomous robotic missions. The methodology encompasses several key steps: defining initial and target conditions, structuring tasks and subtasks, planning their sequence, representing task-related data in a knowledge graph, and designing the mission using a high-level language. Each step builds on the previous one to ensure a cohesive process from initial setup to final execution. A practical implementation within the Aerostack2 framework is demonstrated through a simulated search and rescue mission in a Gazebo environment, where drones autonomously locate a target. This implementation highlights the effectiveness of the methodology in improving decision-making and mission performance by leveraging knowledge graphs.

关键词： Accuracy Robot kinematics System performance Decision making Knowledge graphs Real-time systems Cognition Planning Data mining Drones

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Flocking Behavior for Dynamic and Complex Swarm Structures

Flocking Behavior for Dynamic and Complex Swarm Structures

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Carmen Pita-Romero Pedro Arias-Perez Miguel Fernandez-Cortizas Rafael Perez-Segui Pascual Campoy Computer Vision and Aerial Robotics group (CVAR) Centre for Automation and Robotics (CAR) Universidad Politécnica de Madrid (UPM-CSIC) Madrid Spain

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Maintaining the formation of complex structures with multiple UAVs and achieving complex trajectories remains a major challenge. This work presents an algorithm for implementing the flocking behavior of UAVs based on the concept of Virtual Centroid to easily develop a structure for the flock. The approach builds on the classical virtual-based behavior, providing a theoretical framework for incorporating enhancements to dynamically control both the number of agents and the formation of the structure. Simulation tests and real-world experiments were conducted, demonstrating its simplicity even with complex formations and complex trajectories.

关键词： Heuristic algorithms Trajectory Aircraft

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An aerial/Ground Robot Team for Autonomous Firefighting in Urban GNSS-Denied Scenarios

Field Robotics

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Field robotics 2025年 2卷 241-273页

作者： Simón Martínez-Rozas Rafael Rey David Alejo Domingo Acedo José Antonio Cobano Alejandro Rodríguez-Ramos Pascual Campoy Luis Merino Fernando Caballero Service Robotics Laboratory Universidad Pablo de Olavide Crta. Utrera km. 1 41013 Sevilla Spain Computer Vision and Aerial Robotics Group Centre for Automation and Robotics (C.A.R.) Universidad Politécnica de Madrid (UPM-CSIC) Calle Jose Gutierrez Abascal 2 28006 Madrid Spain

This paper presents a framework for urban firefighting with a heterogeneous aerial/ground robot team. The system was developed to address Challenge 3 of the MBZIRC'20. The challenge required autonomously detecting, locating, and extinguishing fires on multiple interior floors and on exterior facade and ground surfaces. Our multi-robot system consists of a robot team of up to three Unmanned aerial Vehicles (UAV) and one Unmanned Ground Vehicle (UGV). We describe the main hardware and software components for UAV and UGV platforms and present the system's main algorithmic components: a 3D LIDAR-based Mapping and Localization module able to work in GPS-denied scenarios, a Global Planner and a fast local re-planning system for robot navigation, Infrared-Based Perception and robot actuation control for fire extinguishing, and Mission Executive and coordination module based on Behavior Trees. Finally we describe our results from the competition, where the system worked fully autonomously and scored in all the trials performed. The presented system ended in 7 th place (out of 20 teams) in Challenge 3 and 5 th place (out of 17 teams) in the Grand Challenge's Challenge 3 portion.

关键词： Robots Robot kinematics Buildings Robot sensing systems Navigation Autonomous aerial vehicles Sensors Hardware Global Positioning System Autonomous robots

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A Virtual Spring-Damper Approach for UAV Swarm Formation and Decentralised Collision Avoidance

A Virtual Spring-Damper Approach for UAV Swarm Formation and...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Luis Mejias Pedro Arias-Perez Javier Melero-Deza Pascual Campoy The School of Electrical Engineering and Robotics Queens-land University of Technology (QUT) Brisbane QLD Australia The Computer Vision and Aerial Robotics Group Centre for Automation and Robotics (C.A.R.) Universidad Politecnica de Madrid (UPM-CSIC) Madrid Spain

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

This paper introduces a method for controlling UAV swarm formations and avoiding collisions using the Virtual Spring-Damper (VSD) approach. This approach draws upon classical mechanical spring-damper systems, employing displacement and velocities to generate attractive and repulsive forces. These forces help sustain swarm formation and prevent collisions in a decentralized manner. Extensive simulations provided a systematic approach to obtain the parameters involved in the spring-damper system. Flight tests were carried out to verify the proposed method. The experimental outcomes align with our simulations, demonstrating effectiveness in collision avoidance while preserving a specified flight formation.

关键词： Systematics Autonomous aerial vehicles Trajectory Collision avoidance Aircraft Drones Testing

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Exploring Unstructured Environments using Minimal Sensing on Cooperative Nano-Drones

arXiv

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arXiv 2024年

作者： Arias-Perez, Pedro Gautam, Alvika Fernandez-Cortizas, Miguel Perez-Saura, David Saripalli, Srikanth Campoy, Pascual The Computer Vision and Aerial Robotics Group Universidad Politécnica de Madrid Spain Spain The Department of Mechanical Engineering Texas A&M University College StationTX United States

Recent advances have improved autonomous navigation and mapping under payload constraints, but current multi-robot inspection algorithms are unsuitable for nano-drones due to their need for heavy sensors and high computational resources. To address these challenges, we introduce ExploreBug, a novel hybrid frontier range bug algorithm designed to handle limited sensing capabilities for a swarm of nano-drones. This system includes three primary components: a mapping subsystem, an exploration subsystem, and a navigation subsystem. Additionally, an intra-swarm collision avoidance system is integrated to prevent collisions between drones. We validate the efficacy of our approach through extensive simulations and real-world exploration experiments involving up to seven drones in simulations and three in real-world settings, across various obstacle configurations and with a maximum navigation speed of 0.75 m/s. Our tests demonstrate that the algorithm efficiently completes exploration tasks, even with minimal sensing, across different swarm sizes and obstacle densities. Furthermore, our frontier allocation heuristic ensures an equal distribution of explored areas and paths traveled by each drone in the swarm. We publicly release the source code of the proposed system to foster further developments in mapping and exploration using autonomous nano drones. Video: https://***/cvarupm/cf-exploration Code: https://***/pariaspe/cf_exploration © 2024, CC BY.

关键词： Mapping

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Local Gaussian Modifiers (LGMs): UAV Dynamic Trajectory Generation for Onboard Computation

Local Gaussian Modifiers (LGMs): UAV Dynamic Trajectory Gene...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Miguel Fernandez-Cortizas David Perez-Saura Rafael Perez-Segui Javier Rodriguez-Vazquez Juan S. Cely Pascual Campoy Computer Vision and Aerial Robotics group (CVAR) Centre for Automation and Robotics (CAR) Universidad Politécnica de Madrid (UPM) Madrid Spain Department of Artificial Intelligence Universidad Politécnica de Madrid Madrid Spain Intelligent Robotics Lab Rey Juan Carlos University Madrid Spain

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

Agile autonomous drones are becoming increasingly popular in research due to the challenges they represent in fields like control, state estimation, or perception at high speeds. When all algorithms are computed onboard the UAV, computational limitations make the task of agile flight even more difficult. One of the most computationally expensive tasks in agile flight is the generation of optimal trajectories. When these trajectories must be updated online due to changes in the environment or uncertainties, this high computational cost may result in insufficient time to reach the desired waypoints, which could cause a drone crash in cluttered environments. In this paper, we present Local Gaussian Modifiers (LGMs), a fast and lightweight way of modifying computationally heavy trajectories when recalculating them in time is not possible due to computational limitations. Moreover, we propose a strategy for deciding when is convenient to use these modifiers or recalculate the whole trajectory based on an estimation of the computational time of this trajectory generation. A trajectory blending procedure is also proposed to ensure smoothness in UAV control when a new trajectory is computed. Our approach was validated in simulation, being able to pass through a race circuit with moving gates, achieving speeds up to 16.0 m/s. Real flight validation was also performed achieving speeds up to 4.0 m/s in a fully autonomous pipeline using onboard computing.

关键词： Uncertainty Pipelines Logic gates Autonomous aerial vehicles Robustness Motion capture Trajectory

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Micro UAV Swarm for industrial applications in indoor environment – A Systematic Literature Review

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Logistics Research 2023年第1期16卷

作者： Awasthi, Shrutarv Fernandez-Cortizas, Miguel Reining, Christopher Arias-Perez, Pedro Luna, Marco Andres Perez-Saura, David Roidl, Moritz Gramse, Nils Klokowski, Patrick Campoy, Pascual Material Handling and Warehousing Technical University Dortmund Joseph-von-Fraunhofer-Straße 2-4 Dortmund44227 Germany Computer Vision and Aerial Robotics Group Centre for Automation and Robotics UPM-CSIC Universidad Politécnica de Madrid Calle José Gutiérrez Abascal 2 Madrid28006 Spain Joseph-von-Fraunhofer-Straße 2-4 Dortmund Germany

This contribution provides a systematic literature review of micro aerial vehicle (MAV) swarms for indoor industrial applications. First, an initial list of 1997 publications that complies with predefined inclusion criteria was surveyed by reviewers. Next, 185 publications that comply with the Selection Process were analyzed based on localization, control, guidance system, safety and security, MAV charging, communication, artificial intelligence, and applications. The analyzed researches could possibly be deployed in the industrial application of production, logistics and supply chain or transferable into this field. The publications encompassed within this study can be classified under Technology Readiness Level (TRL) 4. Some works do strive to offer solutions tailored to industrial tasks, the validation of their findings predominantly occurs through simulations or controlled laboratory environments. The findings provide an overview of the state-of-the-art specifications, the technologies used by MAVs, trends and outline a future road map for further research from a practitioner’s perspective. © The Author(s) 2023.

关键词： Supply chains

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Spiral coverage path planning for Multi-UAV photovoltaic panel inspection applications

Spiral coverage path planning for Multi-UAV photovoltaic pan...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Marco Andrés Luna Mohammad Sadeq Ale Isaac Miguel Fernandez-Cortizas Carlos Santos Ahmed Refaat Ragab Martin Molina Pascual Campoy Computer Vision and Aerial Robotics Group (CVAR) Centre for Automation and Robotics (C.A.R.) Universidad Politécnica de Madrid (UPM-CSIC) Madrid Spain Department of Signal Theory and Communications University of Alcala (UAH) Madrid Spain Department of Network Faculty of Information Systems and Computer Science October 6 University Giza Egypt Department of Artificial Intelligence Universidad Politécnica de Madrid Madrid Spain

This paper deals with the problem of coverage path planning for multiple UAVs in disjoint regions. For this purpose, a spiral-coverage path planning algorithm is proposed. Additionally, task assignment methods for multi-region inspection with a swarm of UAVs are applied. The centralized system architecture is described, and an adaptive sliding mode controller is designed. Furthermore, we evaluate the performance of the proposed techniques by obtaining numerical results and simulations with the controller. The results show that the spiral pattern optimizes the cost of the mission and improves the task distribution of the mission planning system. Additionally, the performance of the proposed controller is robust to simulated disturbances.

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Errata: Mathematical Modeling and Designing a Heavy Hybrid-Electric Quadcopter, Controlled by Flaps

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Unmanned Systems 2024年第1期12卷 183-183页

作者： Mohammad Sadeq Ale Isaac Ahmed Refaat Ragab Enrique Caballero Garcés Marco Andres Luna Pablo Flores Peña Pascual Campoy Cervera Drone Hopper Company Spain Computer Vision and Aerial Robotics Group at Universidad Politécnica de Madrid (CVAR-UPM) at Centre for Automation and Robotics C.A.R. (UPM-CSIC) Spain University of Carlos III of Madrid Spain UC3M and Aerodynamics Engineer at Drone Hopper Spain

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Towards multi-object detection and tracking in urban scenario under uncertainties 4

Towards multi-object detection and tracking in urban scenari...

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4th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2018

作者： Kampker, Achim Sefati, Mohsen Abdul Rachman, Arya S. Kreisköther, Kai Campoy, Pascual Chair of Production Engineering of E-Mobility Components RWTH Aachen University Aachen Germany Delft Center for Systems and Control Delft University of Technology Delft Netherlands Computer Vision and Aerial Robotics Group Centre of Automatics and Robotics Universidad Politécnica de Madrid Madrid Spain

ISBN: (纸本)9789897582936

Urban-oriented autonomous vehicles require a reliable perception technology to tackle the high amount of uncertainties. The recently introduced compact 3D LIDAR sensor offers a surround spatial information that can be exploited to enhance the vehicle perception. We present a real-time integrated framework of multi-target object detection and tracking using 3D LIDAR geared toward urban use. Our approach combines sensor occlusion-aware detection method with computationally efficient heuristics rule-based filtering and adaptive probabilistic tracking to handle uncertainties arising from sensing limitation of 3D LIDAR and complexity of the target object movement. The evaluation results using real-world pre-recorded 3D LIDAR data and comparison with state-of-the-art works shows that our framework is capable of achieving promising tracking performance in the urban situation. Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Autonomous vehicles

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