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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Alejandro Olivas Miguel Ángel Muñoz-Bañón Edison Velasco Fernando Torres Group of Automation Robotics and Computer Vision (AUROVA) University of Alicante Alicante Spain

The tracking problem remains difficult because trackers may lose the target due to occlusions or changes in the target's appearance and start tracking another one, making it difficult to detect when they fail. To deal with these problems, we design a novel method to track objects robustly by fusing different trackers, using an Extended Kalman Filter, which helps to detect these situations and correct them. We use our tracker-fusion in a mobile robot to follow a pedestrian while also avoiding dynamic obstacles, an aspect not usually analyzed in pedestrian following. The perception of the environment is done with a 3D LiDAR and the tracking is performed on front-view images constructed from the point cloud. We show that by fusing two different trackers, the robot can follow the target during long experimental sessions where there are occlusions of the target by other people. The method is more precise and robust than using the trackers without the fusion.

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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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A Methodology for Designing Knowledge-Driven Missions for Robots

A Methodology for Designing Knowledge-Driven Missions for Ro...

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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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LiLO: Lightweight and low-bias LiDAR Odometry method based on spherical range image filtering

arXiv

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arXiv 2023年

作者： Velasco-Sánchez, Edison P. Ángel Muñoz-Bañón, Miguel Candelas, Francisco A. Puente, Santiago T. Torres, Fernando The Group of Automation Robotics and Computer Vision AUROVA University of Alicante San Vicente del Raspeig Alicante03690 Spain

In unstructured outdoor environments, robotics requires accurate and efficient odometry with low computational time. Existing low-bias LiDAR odometry methods are often computationally expensive. To address this problem, we present a lightweight LiDAR odometry method that converts unorganized point cloud data into a spherical range image (SRI) and filters out surface, edge, and ground features in the image plane. This substantially reduces computation time and the required features for odometry estimation in LOAM-based algorithms. Our odometry estimation method does not rely on global maps or loop closure algorithms, which further reduces computational costs. Experimental results generate a translation and rotation error of 0.86% and 0.0036°/m on the KITTI dataset with an average runtime of 78ms. In addition, we tested the method with our data, obtaining an average closed-loop error of 0.8m and a runtime of 27ms over eight loops covering 3.5Km. The code is available at: https://***/AUROVA-LAB/applications. © 2023, CC0.

关键词： Robot applications

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Lo-Fri: Lidar Odometry Based on Filtered Range Images

SSRN

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SSRN 2023年

作者： Velasco-Sánchez, Edison P. Muñoz-Bañón, Miguel Á. Candelas-Herias, Francisco A. Puente-Mendez, Santiago T. Torres-Medina, Fernando AUROVA Group of Automation Robotics and Computer Vision University of Alicante San Vicente del Raspeig S/N Alicante03690 Spain

Robotic localization in unstructured outdoor environments is increasingly in need of low-bias and computationally efficient odometry methods. In this paper, we propose a LiDAR odometry process based on filtered range images with point-to-edge and point-to-plane ICP matching. This method separates edges, surfaces and ground features from a point cloud with gradient image filtering methods. Besides, we present a filter based on a Fourier mask that separates the fundamental frequencies of the image that correspond to the ground plane. The evaluation results generate a translation and rotation error of 0.86% and 0.0036°/m on the KITTI training data set and a runtime of 78 ms. In addition, the system was tested on a UGV with a Velodyne VLP-16 sensor, yielding an average closed-loop error of 0.8 m and a runtime of 27 ms over eight loops covering 3.5 km. © 2023, The Authors. All rights reserved.

关键词： Optical radar

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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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Operator as a Service: A New Concept for Remote Supervision of Automated Manufacturing Lines

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IEEE Access 2025年 13卷 93661-93671页

作者： Marco Ojer Sergio Valdés Ander Garcia Xabier Oregui Iker Gastesi Xiao Lin Iñigo Mendizabal-Arrieta Jairo R. Sanchez Elena Lazkano Vicomtech Foundation Basque Research and Technology Alliance (BRTA) Donostia-San Sebastian Spain Computer Science and Artificial Intelligence Department University of the Basque Country (UPV/EHU) Donostia-San Sebastian Spain Group of Automation Robotics and Computer Vision (AUROVA) University of Alicante Alicante Spain

This paper introduces the Operator as a Service (OaaS) concept, a novel paradigm for human labour in the era of Industry 4.0. OaaS empowers skilled operators to remotely oversee and control multiple flexible smart manufacturing lines through advanced technologies such as digital twins and remote collaboration. By transitioning from on-site, full-time operators to specialized remote operators available on demand, OaaS optimizes human resource utilization and facilitates the transition towards more flexible and responsive manufacturing systems. This paper presents the OaaS architecture, discusses its potential benefits for enhancing operational efficiency and adaptability in semi-controlled manufacturing environments, and validates its feasibility through a real-world testbed involving a fully automated assembly line. The results demonstrate the potential of OaaS to address the challenges of maintaining human oversight and ensuring operational flexibility in increasingly complex and interconnected manufacturing systems.

关键词： Manufacturing Digital twins Robots Production facilities Manufacturing processes Fourth Industrial Revolution Service-oriented architecture Real-time systems Artificial intelligence Costs

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DualQuat-LOAM: LiDAR Odometry and Mapping parametrized on Dual Quaternions

arXiv

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arXiv 2024年

作者： Velasco-Sánchez, Edison P. Recalde, Luis F. Li, Guanrui Candelas-Herias, Francisco A. Puente-Mendez, Santiago T. Torres-Medina, Fernando AUROVA Group of Automation Robotics and Computer Vision University of Alicante San Vicente del Raspeig S/N Alicante03690 Spain Worcester Polytechnic Institute Worcester01609 United States

This paper reports on a novel method for LiDAR odometry estimation, which completely parameterizes the system with dual quaternions. To accomplish this, the features derived from the point cloud, including edges, surfaces, and Stable Triangle Descriptor (STD), along with the optimization problem, are expressed in the dual quaternion set. This approach enables the direct combination of translation and orientation errors via dual quaternion operations, greatly enhancing pose estimation, as demonstrated in comparative experiments against other state-of-the-art methods. Our approach reduced drift error compared to other LiDAR-only-odometry methods, especially in scenarios with sharp curves and aggressive movements with large angular displacement. DualQuat-LOAM is benchmarked against several public datasets. In the KITTI dataset it has a translation and rotation error of 0.79% and 0.0039°/m, with an average run time of 53 ms. © 2024, CC BY-NC-ND.

关键词： robotics

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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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