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Dr. Jose Luis Sanchez-Lopez
University of Luxembourg

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0 Robotics
0 Situational Awareness
0 SLAM
0 Drones
0 aerial robots

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aerial robots
Drones

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Conference paper
Published: 01 September 2020 in 2020 International Conference on Unmanned Aircraft Systems (ICUAS)
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In this work, we present a semantic situation awareness system for multirotor aerial robots equipped with a 2D LIDAR sensor, focusing on the understanding of the environment, provided to have a drift-free precise localization of the robot (e.g. given by GNSS/INS or motion capture system). Our algorithm generates in real-time a semantic map of the objects of the environment as a list of ellipses represented by their radii, and their pose and velocity, both in world coordinates. Two different Convolutional Neural Network (CNN) architectures are proposed and trained using an artificially generated dataset and a custom loss function, to detect ellipses in a segmented (i.e. with one single object) LIDAR measurement. In cascade, a specifically designed indirect-EKF estimates the ellipses based semantic map in world coordinates, as well as their velocity. We have quantitative and qualitatively evaluated the performance of our proposed situation awareness system. Two sets of Software-In-The-Loop simulations using CoppeliaSim with one and multiple static and moving cylindrical objects are used to evaluate the accuracy and performance of our algorithm. In addition, we have demonstrated the robustness of our proposed algorithm when handling real environments thanks to real laboratory experiments with non-cylindrical static (i.e. a barrel) objects and moving persons.

ACS Style

Jose Luis Sanchez-Lopez; Manuel Castillo-Lopez; Holger Voos. Semantic situation awareness of ellipse shapes via deep learning for multirotor aerial robots with a 2D LIDAR. 2020 International Conference on Unmanned Aircraft Systems (ICUAS) 2020, 1014 -1023.

AMA Style

Jose Luis Sanchez-Lopez, Manuel Castillo-Lopez, Holger Voos. Semantic situation awareness of ellipse shapes via deep learning for multirotor aerial robots with a 2D LIDAR. 2020 International Conference on Unmanned Aircraft Systems (ICUAS). 2020; ():1014-1023.

Chicago/Turabian Style

Jose Luis Sanchez-Lopez; Manuel Castillo-Lopez; Holger Voos. 2020. "Semantic situation awareness of ellipse shapes via deep learning for multirotor aerial robots with a 2D LIDAR." 2020 International Conference on Unmanned Aircraft Systems (ICUAS) , no. : 1014-1023.

Review
Published: 04 August 2020 in Journal of Imaging
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The spread of Unmanned Aerial Vehicles (UAVs) in the last decade revolutionized many applications fields. Most investigated research topics focus on increasing autonomy during operational campaigns, environmental monitoring, surveillance, maps, and labeling. To achieve such complex goals, a high-level module is exploited to build semantic knowledge leveraging the outputs of the low-level module that takes data acquired from multiple sensors and extracts information concerning what is sensed. All in all, the detection of the objects is undoubtedly the most important low-level task, and the most employed sensors to accomplish it are by far RGB cameras due to costs, dimensions, and the wide literature on RGB-based object detection. This survey presents recent advancements in 2D object detection for the case of UAVs, focusing on the differences, strategies, and trade-offs between the generic problem of object detection, and the adaptation of such solutions for operations of the UAV. Moreover, a new taxonomy that considers different heights intervals and driven by the methodological approaches introduced by the works in the state of the art instead of hardware, physical and/or technological constraints is proposed.

ACS Style

Dario Cazzato; Claudio Cimarelli; Jose Luis Sanchez-Lopez; Holger Voos; Marco Leo. A Survey of Computer Vision Methods for 2D Object Detection from Unmanned Aerial Vehicles. Journal of Imaging 2020, 6, 78 .

AMA Style

Dario Cazzato, Claudio Cimarelli, Jose Luis Sanchez-Lopez, Holger Voos, Marco Leo. A Survey of Computer Vision Methods for 2D Object Detection from Unmanned Aerial Vehicles. Journal of Imaging. 2020; 6 (8):78.

Chicago/Turabian Style

Dario Cazzato; Claudio Cimarelli; Jose Luis Sanchez-Lopez; Holger Voos; Marco Leo. 2020. "A Survey of Computer Vision Methods for 2D Object Detection from Unmanned Aerial Vehicles." Journal of Imaging 6, no. 8: 78.

Article
Published: 22 July 2020 in Journal of Intelligent & Robotic Systems
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In this work, we present an optimization-based trajectory tracking solution for multirotor aerial robots given a geometrically feasible path. A trajectory planner generates a minimum-time kinematically and dynamically feasible trajectory that includes not only standard restrictions such as continuity and limits on the trajectory, constraints in the waypoints, and maximum distance between the planned trajectory and the given path, but also restrictions in the actuators of the aerial robot based on its dynamic model, guaranteeing that the planned trajectory is achievable. Our novel compact multi-phase trajectory definition, as a set of two different kinds of polynomials, provides a higher semantic encoding of the trajectory, which allows calculating an optimal solution but following a predefined simple profile. A Model Predictive Controller ensures that the planned trajectory is tracked by the aerial robot with the smallest deviation. Its novel formulation takes as inputs all the magnitudes of the planned trajectory (i.e. position and heading, velocity, and acceleration) to generate the control commands, demonstrating through in-lab real flights an improvement of the tracking performance when compared with a controller that only uses the planned position and heading. To support our optimization-based solution, we discuss the most commonly used representations of orientations, as well as both the difference as well as the scalar error between two rotations, in both tridimensional and bidimensional spaces SO(3) and SO(2). We demonstrate that quaternions and error-quaternions have some advantages when compared to other formulations.

ACS Style

Jose Luis Sanchez-Lopez; Manuel Castillo-Lopez; Miguel A. Olivares-Mendez; Holger Voos. Trajectory Tracking for Aerial Robots: an Optimization-Based Planning and Control Approach. Journal of Intelligent & Robotic Systems 2020, 100, 1 -44.

AMA Style

Jose Luis Sanchez-Lopez, Manuel Castillo-Lopez, Miguel A. Olivares-Mendez, Holger Voos. Trajectory Tracking for Aerial Robots: an Optimization-Based Planning and Control Approach. Journal of Intelligent & Robotic Systems. 2020; 100 (2):1-44.

Chicago/Turabian Style

Jose Luis Sanchez-Lopez; Manuel Castillo-Lopez; Miguel A. Olivares-Mendez; Holger Voos. 2020. "Trajectory Tracking for Aerial Robots: an Optimization-Based Planning and Control Approach." Journal of Intelligent & Robotic Systems 100, no. 2: 1-44.

Journal article
Published: 21 February 2020 in IEEE Robotics and Automation Letters
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Uncertain dynamic obstacles such as pedestrians or vehicles pose a major challenge for optimal robot navigation with safety guarantees. Previous work on motion planning have followed two main strategies to provide a safe bound on an obstacle's space: a polyhedron, such as a cuboid, or a nonlinear differentiable surface, such as an ellipsoid. The former approach relies on disjunctive programming, which has a relatively high computational cost that grows exponentially with the number of obstacles. The latter approach needs to be linearized locally to find a tractable evaluation of the chance constraints, which dramatically reduces the remaining free space and leads to over-conservative trajectories or even unfeasibility. In this work, we present a hybrid approach that eludes the pitfalls of both strategies while maintaining the original safety guarantees. The key idea consists in obtaining a safe differentiable approximation for the disjunctive chance constraints bounding the obstacles. The resulting nonlinear optimization problem is free of chance constraint linearization and disjunctive programming, and therefore, it can be efficiently solved to meet fast real-time requirements with multiple obstacles. We validate our approach through mathematical proof, simulation and real experiments with an aerial robot using nonlinear model predictive control to avoid pedestrians.

ACS Style

Manuel Castillo-Lopez; Philippe Ludivig; Seyed Amin Sajadi-Alamdari; Jose Luis Sanchez-Lopez; Miguel A. Olivares-Mendez; Holger Voos. A Real-Time Approach for Chance-Constrained Motion Planning With Dynamic Obstacles. IEEE Robotics and Automation Letters 2020, 5, 3620 -3625.

AMA Style

Manuel Castillo-Lopez, Philippe Ludivig, Seyed Amin Sajadi-Alamdari, Jose Luis Sanchez-Lopez, Miguel A. Olivares-Mendez, Holger Voos. A Real-Time Approach for Chance-Constrained Motion Planning With Dynamic Obstacles. IEEE Robotics and Automation Letters. 2020; 5 (2):3620-3625.

Chicago/Turabian Style

Manuel Castillo-Lopez; Philippe Ludivig; Seyed Amin Sajadi-Alamdari; Jose Luis Sanchez-Lopez; Miguel A. Olivares-Mendez; Holger Voos. 2020. "A Real-Time Approach for Chance-Constrained Motion Planning With Dynamic Obstacles." IEEE Robotics and Automation Letters 5, no. 2: 3620-3625.

Conference paper
Published: 01 October 2019 in IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
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The reliability of aircraft inspection is of paramount importance to safety of flights. Continuing airworthiness of aircraft structures is largely based upon the visual detection of small defects made by trained inspection personnel with expensive, critical and time consuming tasks. At this aim, Unmanned Aerial Vehicles (UAVs) can be used for autonomous inspections, as long as it is possible to localize the target while flying around it and correct the position. This work proposes a solution to detect the airplane pose with regards to the UAVs position while flying autonomously around the airframe at close range for visual inspection tasks. The system works by processing images coming from an RGB camera mounted on board, comparing incoming frames with a database of natural landmarks whose position on the airframe surface is known. The solution has been tested in real UAV flight scenarios, showing its effectiveness in localizing the pose with high precision. The advantages of the proposed methods are of industrial interest since we remove many constraint that are present in the state of the art solutions.

ACS Style

Dario Cazzato; Miguel A. Olivares-Mendez; Jose Luis Sanchez-Lopez; Holger Voos. Vision-Based Aircraft Pose Estimation for UAVs Autonomous Inspection without Fiducial Markers. IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society 2019, 1, 5642 -5648.

AMA Style

Dario Cazzato, Miguel A. Olivares-Mendez, Jose Luis Sanchez-Lopez, Holger Voos. Vision-Based Aircraft Pose Estimation for UAVs Autonomous Inspection without Fiducial Markers. IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society. 2019; 1 ():5642-5648.

Chicago/Turabian Style

Dario Cazzato; Miguel A. Olivares-Mendez; Jose Luis Sanchez-Lopez; Holger Voos. 2019. "Vision-Based Aircraft Pose Estimation for UAVs Autonomous Inspection without Fiducial Markers." IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society 1, no. : 5642-5648.

Conference paper
Published: 01 June 2019 in 2019 International Conference on Unmanned Aircraft Systems (ICUAS)
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In this work, we present a semantic situation awareness system for multirotor aerial robots, based on 2D LIDAR measurements, targeting the understanding of the environment and assuming to have a precise robot localization as an input of our algorithm. Our proposed situation awareness system calculates a semantic map of the objects of the environment as a list of circles represented by their radius, and the position and the velocity of their center in world coordinates. Our proposed algorithm includes three main parts. First, the LIDAR measurements are preprocessed and an object segmentation clusters the candidate objects present in the environment. Secondly, a Convolutional Neural Network (CNN) that has been designed and trained using an artificially generated dataset, computes the radius and the position of the center of individual circles in sensor coordinates. Finally, an indirect-EKF provides the estimate of the semantic map in world coordinates, including the velocity of the center of the circles in world coordinates.We have quantitative and qualitative evaluated the performance of our proposed situation awareness system by means of Software-In-The-Loop simulations using VRep with one and multiple static and moving cylindrical objects in the scene, obtaining results that support our proposed algorithm. In addition, we have demonstrated that our proposed algorithm is capable of handling real environments thanks to real laboratory experiments with non-cylindrical static (i.e. a barrel) and moving (i.e. a person) objects.

ACS Style

Jose Luis Sanchez-Lopez; Carlos Sampedro; Dario Cazzato; Holger Voos. Deep learning based semantic situation awareness system for multirotor aerial robots using LIDAR. 2019 International Conference on Unmanned Aircraft Systems (ICUAS) 2019, 899 -908.

AMA Style

Jose Luis Sanchez-Lopez, Carlos Sampedro, Dario Cazzato, Holger Voos. Deep learning based semantic situation awareness system for multirotor aerial robots using LIDAR. 2019 International Conference on Unmanned Aircraft Systems (ICUAS). 2019; ():899-908.

Chicago/Turabian Style

Jose Luis Sanchez-Lopez; Carlos Sampedro; Dario Cazzato; Holger Voos. 2019. "Deep learning based semantic situation awareness system for multirotor aerial robots using LIDAR." 2019 International Conference on Unmanned Aircraft Systems (ICUAS) , no. : 899-908.

Conference paper
Published: 01 January 2019 in Proceedings of the 2019 3rd International Conference on Artificial Intelligence and Virtual Reality - AIVR 2019
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ACS Style

Dario Cazzato; Claudio Cimarelli; Jose Luis Sanchez-Lopez; Miguel A. Olivares-Mendez; Holger Voos. Real-Time Human Head Imitation for Humanoid Robots. Proceedings of the 2019 3rd International Conference on Artificial Intelligence and Virtual Reality - AIVR 2019 2019, 65 -69.

AMA Style

Dario Cazzato, Claudio Cimarelli, Jose Luis Sanchez-Lopez, Miguel A. Olivares-Mendez, Holger Voos. Real-Time Human Head Imitation for Humanoid Robots. Proceedings of the 2019 3rd International Conference on Artificial Intelligence and Virtual Reality - AIVR 2019. 2019; ():65-69.

Chicago/Turabian Style

Dario Cazzato; Claudio Cimarelli; Jose Luis Sanchez-Lopez; Miguel A. Olivares-Mendez; Holger Voos. 2019. "Real-Time Human Head Imitation for Humanoid Robots." Proceedings of the 2019 3rd International Conference on Artificial Intelligence and Virtual Reality - AIVR 2019 , no. : 65-69.

Journal article
Published: 06 September 2018 in Aerospace
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This paper presents a fast and robust approach for estimating the flight altitude of multirotor Unmanned Aerial Vehicles (UAVs) using 3D point cloud sensors in cluttered, unstructured, and dynamic indoor environments. The objective is to present a flight altitude estimation algorithm, replacing the conventional sensors such as laser altimeters, barometers, or accelerometers, which have several limitations when used individually. Our proposed algorithm includes two stages: in the first stage, a fast clustering of the measured 3D point cloud data is performed, along with the segmentation of the clustered data into horizontal planes. In the second stage, these segmented horizontal planes are mapped based on the vertical distance with respect to the point cloud sensor frame of reference, in order to provide a robust flight altitude estimation even in presence of several static as well as dynamic ground obstacles. We validate our approach using the IROS 2011 Kinect dataset available in the literature, estimating the altitude of the RGB-D camera using the provided 3D point clouds. We further validate our approach using a point cloud sensor on board a UAV, by means of several autonomous real flights, closing its altitude control loop using the flight altitude estimated by our proposed method, in presence of several different static as well as dynamic ground obstacles. In addition, the implementation of our approach has been integrated in our open-source software framework for aerial robotics called Aerostack.

ACS Style

Hriday Bavle; Jose Luis Sanchez-Lopez; Paloma De La Puente; Alejandro Rodriguez-Ramos; Carlos Sampedro; Pascual Campoy. Fast and Robust Flight Altitude Estimation of Multirotor UAVs in Dynamic Unstructured Environments Using 3D Point Cloud Sensors. Aerospace 2018, 5, 94 .

AMA Style

Hriday Bavle, Jose Luis Sanchez-Lopez, Paloma De La Puente, Alejandro Rodriguez-Ramos, Carlos Sampedro, Pascual Campoy. Fast and Robust Flight Altitude Estimation of Multirotor UAVs in Dynamic Unstructured Environments Using 3D Point Cloud Sensors. Aerospace. 2018; 5 (3):94.

Chicago/Turabian Style

Hriday Bavle; Jose Luis Sanchez-Lopez; Paloma De La Puente; Alejandro Rodriguez-Ramos; Carlos Sampedro; Pascual Campoy. 2018. "Fast and Robust Flight Altitude Estimation of Multirotor UAVs in Dynamic Unstructured Environments Using 3D Point Cloud Sensors." Aerospace 5, no. 3: 94.

Conference paper
Published: 01 June 2018 in 2018 International Conference on Unmanned Aircraft Systems (ICUAS)
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Planning feasible trajectories given desired collision-free paths is an essential capability of multirotor aerial robots that enables the trajectory tracking task, in contrast to path following. This paper presents a trajectory planner for multirotor aerial robots carefully designed considering the requirements of real applications such as aerial inspection or package delivery, unlike other research works that focus on aggressive maneuvering. Our planned trajectory is formed by a set of polynomials of two kinds, acceleration/deceleration and constant velocity. The trajectory planning is carried out by means of an optimization that minimizes the trajectory tracking time, applying some typical constraints as m-continuity or limits on velocity, acceleration and jerk, but also the maximum distance between the trajectory and the given path. Our trajectory planner has been tested in real flights with a big and heavy aerial platform such the one that would be used in a real operation. Our experiments demonstrate that the proposed trajectory planner is suitable for real applications and it is positively influencing the controller for the trajectory tracking task.

ACS Style

Jose Luis Sanchez-Lopez; Miguel A. Olivares-Mendez; Manuel Castillo-Lopez; Holger Voos. Towards trajectory planning from a given path for multirotor aerial robots trajectory tracking. 2018 International Conference on Unmanned Aircraft Systems (ICUAS) 2018, 1342 -1351.

AMA Style

Jose Luis Sanchez-Lopez, Miguel A. Olivares-Mendez, Manuel Castillo-Lopez, Holger Voos. Towards trajectory planning from a given path for multirotor aerial robots trajectory tracking. 2018 International Conference on Unmanned Aircraft Systems (ICUAS). 2018; ():1342-1351.

Chicago/Turabian Style

Jose Luis Sanchez-Lopez; Miguel A. Olivares-Mendez; Manuel Castillo-Lopez; Holger Voos. 2018. "Towards trajectory planning from a given path for multirotor aerial robots trajectory tracking." 2018 International Conference on Unmanned Aircraft Systems (ICUAS) , no. : 1342-1351.

Article
Published: 07 April 2018 in Journal of Intelligent & Robotic Systems
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Deliberative capabilities are essential for intelligent aerial robotic applications in modern life such as package delivery and surveillance. This paper presents a real-time 3D path planning solution for multirotor aerial robots to obtain a feasible, optimal and collision-free path in complex dynamic environments. High-level geometric primitives are employed to compactly represent the situation, which includes self-situation of the robot and situation of the obstacles in the environment. A probabilistic graph is utilized to sample the admissible space without taking into account the existing obstacles. Whenever a planning query is received, the generated probabilistic graph is then explored by an A⋆ discrete search algorithm with an artificial field map as cost function in order to obtain a raw optimal collision-free path, which is subsequently shortened. Realistic simulations in V-REP simulator have been created to validate the proposed path planning solution, integrating it into a fully autonomous multirotor aerial robotic system.

ACS Style

Jose Luis Sanchez-Lopez; Min Wang; Miguel A. Olivares-Mendez; Martin Molina; Holger Voos. A Real-Time 3D Path Planning Solution for Collision-Free Navigation of Multirotor Aerial Robots in Dynamic Environments. Journal of Intelligent & Robotic Systems 2018, 93, 33 -53.

AMA Style

Jose Luis Sanchez-Lopez, Min Wang, Miguel A. Olivares-Mendez, Martin Molina, Holger Voos. A Real-Time 3D Path Planning Solution for Collision-Free Navigation of Multirotor Aerial Robots in Dynamic Environments. Journal of Intelligent & Robotic Systems. 2018; 93 (1-2):33-53.

Chicago/Turabian Style

Jose Luis Sanchez-Lopez; Min Wang; Miguel A. Olivares-Mendez; Martin Molina; Holger Voos. 2018. "A Real-Time 3D Path Planning Solution for Collision-Free Navigation of Multirotor Aerial Robots in Dynamic Environments." Journal of Intelligent & Robotic Systems 93, no. 1-2: 33-53.

Journal article
Published: 13 November 2017 in International Journal of Intelligent Computing and Cybernetics
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The purpose of this paper is to describe the specification language TML for adaptive mission plans that the authors designed and implemented for the open-source framework Aerostack for aerial robotics. The TML language combines a task-based hierarchical approach together with a more flexible representation, rule-based reactive planning, to facilitate adaptability. This approach includes additional notions that abstract programming details. The authors built an interpreter integrated in the software framework Aerostack. The interpreter was validated with flight experiments for multi-robot missions in dynamic environments. The experiments proved that the TML language is easy to use and expressive enough to formulate adaptive missions in dynamic environments. The experiments also showed that the TML interpreter is efficient to execute multi-robot aerial missions and reusable for different platforms. The TML interpreter is able to verify the mission plan before its execution, which increases robustness and safety, avoiding the execution of certain plans that are not feasible. One of the main contributions of this work is the availability of a reliable solution to specify aerial mission plans, integrated in an active open-source project with periodic releases. To the best knowledge of the authors, there are not solutions similar to this in other active open-source projects. As additional contributions, TML uses an original combination of representations for adaptive mission plans (i.e. task trees with original abstract notions and rule-based reactive planning) together with the demonstration of its adequacy for aerial robotics.

ACS Style

Martin Molina; Ramón A. Suárez Fernández; Carlos Sampedro; Jose Luis Sanchez-Lopez; Pascual Campoy. TML: a language to specify aerial robotic missions for the framework Aerostack. International Journal of Intelligent Computing and Cybernetics 2017, 10, 491 -512.

AMA Style

Martin Molina, Ramón A. Suárez Fernández, Carlos Sampedro, Jose Luis Sanchez-Lopez, Pascual Campoy. TML: a language to specify aerial robotic missions for the framework Aerostack. International Journal of Intelligent Computing and Cybernetics. 2017; 10 (4):491-512.

Chicago/Turabian Style

Martin Molina; Ramón A. Suárez Fernández; Carlos Sampedro; Jose Luis Sanchez-Lopez; Pascual Campoy. 2017. "TML: a language to specify aerial robotic missions for the framework Aerostack." International Journal of Intelligent Computing and Cybernetics 10, no. 4: 491-512.

Journal article
Published: 01 July 2017 in IFAC-PapersOnLine
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ACS Style

Jose Luis Sanchez-Lopez; Victor Arellano-Quintana; Marco Tognon; Pascual Campoy; Antonio Franchi. Visual Marker based Multi-Sensor Fusion State Estimation * *During this work Jose Luis Sanchez-Lopez has been funded by the Eiffel Excellence Scholarship Program of the French Ministry of Foreign Affairs and International Development and Victor Arellano-Quintana has been funded by a scholarship from CONACyT for studies abroad.This work has been partially funded by the European Unions Horizon 2020 research and innovation programme under grant agreement No 644271 AEROARMS. IFAC-PapersOnLine 2017, 50, 16003 -16008.

AMA Style

Jose Luis Sanchez-Lopez, Victor Arellano-Quintana, Marco Tognon, Pascual Campoy, Antonio Franchi. Visual Marker based Multi-Sensor Fusion State Estimation * *During this work Jose Luis Sanchez-Lopez has been funded by the Eiffel Excellence Scholarship Program of the French Ministry of Foreign Affairs and International Development and Victor Arellano-Quintana has been funded by a scholarship from CONACyT for studies abroad.This work has been partially funded by the European Unions Horizon 2020 research and innovation programme under grant agreement No 644271 AEROARMS. IFAC-PapersOnLine. 2017; 50 (1):16003-16008.

Chicago/Turabian Style

Jose Luis Sanchez-Lopez; Victor Arellano-Quintana; Marco Tognon; Pascual Campoy; Antonio Franchi. 2017. "Visual Marker based Multi-Sensor Fusion State Estimation * *During this work Jose Luis Sanchez-Lopez has been funded by the Eiffel Excellence Scholarship Program of the French Ministry of Foreign Affairs and International Development and Victor Arellano-Quintana has been funded by a scholarship from CONACyT for studies abroad.This work has been partially funded by the European Unions Horizon 2020 research and innovation programme under grant agreement No 644271 AEROARMS." IFAC-PapersOnLine 50, no. 1: 16003-16008.

Conference paper
Published: 01 June 2017 in 2017 International Conference on Unmanned Aircraft Systems (ICUAS)
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A reliable estimation of the flight altitude in dynamic and unstructured indoor environments is an unsolved problem. Standalone available sensors, such as distance sensors, barometers and accelerometers, have multiple limitations in presence of non-flat ground surfaces, or in cluttered areas. To overcome these sensor limitations, maximizing their individual performance, this paper presents a modular EKF-based multi-sensor fusion approach for accurate vertical localization of multirotor UAVs in dynamic and unstructured indoor environments. The state estimator allows to combine the information provided by a variable number and type of sensors, including IMU, barometer and distance sensors, with the capabilities of sensor auto calibration and bias estimation, as well as a flexible configuration of the prediction and update stages. Several autonomous indoors real flights in unstructured environments have been conducted in order to validate our proposed state estimator, enabling the UAV to maintain the desired flight altitude when navigating over wide range of obstacles. Furthermore, it has been successfully used in IMAV 2016 competition. The presented work has been made publicly available to the scientific community as an open source software within the Aerostack 1 framework.

ACS Style

Hriday Bavle; Jose Luis Sanchez-Lopez; Alejandro Rodriguez-Ramos; Carlos Sampedro; Pascual Campoy. A flight altitude estimator for multirotor UAVs in dynamic and unstructured indoor environments. 2017 International Conference on Unmanned Aircraft Systems (ICUAS) 2017, 1044 -1051.

AMA Style

Hriday Bavle, Jose Luis Sanchez-Lopez, Alejandro Rodriguez-Ramos, Carlos Sampedro, Pascual Campoy. A flight altitude estimator for multirotor UAVs in dynamic and unstructured indoor environments. 2017 International Conference on Unmanned Aircraft Systems (ICUAS). 2017; ():1044-1051.

Chicago/Turabian Style

Hriday Bavle; Jose Luis Sanchez-Lopez; Alejandro Rodriguez-Ramos; Carlos Sampedro; Pascual Campoy. 2017. "A flight altitude estimator for multirotor UAVs in dynamic and unstructured indoor environments." 2017 International Conference on Unmanned Aircraft Systems (ICUAS) , no. : 1044-1051.

Conference paper
Published: 01 June 2017 in 2017 International Conference on Unmanned Aircraft Systems (ICUAS)
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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.

ACS Style

Carlos Sampedro; Hriday Bavle; Alejandro Rodriguez-Ramos; Adrian Carrio; Ramón A. Suárez Fernández; Jose Luis Sanchez-Lopez; Pascual Campoy. A fully-autonomous aerial robotic solution for the 2016 International Micro Air Vehicle competition. 2017 International Conference on Unmanned Aircraft Systems (ICUAS) 2017, 989 -998.

AMA Style

Carlos Sampedro, Hriday Bavle, Alejandro Rodriguez-Ramos, Adrian Carrio, Ramón A. Suárez Fernández, Jose Luis Sanchez-Lopez, Pascual Campoy. A fully-autonomous aerial robotic solution for the 2016 International Micro Air Vehicle competition. 2017 International Conference on Unmanned Aircraft Systems (ICUAS). 2017; ():989-998.

Chicago/Turabian Style

Carlos Sampedro; Hriday Bavle; Alejandro Rodriguez-Ramos; Adrian Carrio; Ramón A. Suárez Fernández; Jose Luis Sanchez-Lopez; Pascual Campoy. 2017. "A fully-autonomous aerial robotic solution for the 2016 International Micro Air Vehicle competition." 2017 International Conference on Unmanned Aircraft Systems (ICUAS) , no. : 989-998.

Conference paper
Published: 01 June 2017 in 2017 International Conference on Unmanned Aircraft Systems (ICUAS)
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The development of deliberative capabilities is required to achieve an intelligent fully autonomous behavior of unmanned aerial systems. An important deliberative capability is the generation of collision-free paths in complex environments. This paper presents a robust real-time collision-free path planner used for the horizontal 2D navigation of multirotor aerial robots in dynamic environments. Its design, using geometric primitives to describe the environment combined with a launching time generation of a probabilistic roadmap graph, permits an efficient management of dynamic obstacles. The use of an A* discrete search algorithm, together with a potential field map as the cost function, allows to speed up the collision-free path computation ensuring that it never falls in local minima. Additionally, the velocity and acceleration along the collision-free planned path is calculated. The performance of the proposed path planner is evaluated in this paper with two simulations with complex environments including a labyrinth and dead ends, and with a real flight experiment where three fully autonomous aerial robots executed an emulated search and rescue mission. The proposed path planner has been released to the scientific community as an open-source software included in Aerostack 2 . In addition, it has extensively been used in multiple research projects with real flights, demonstrating its good performance.

ACS Style

Jose Luis Sanchez-Lopez; Jesus Pestana; Pascual Campoy. A robust real-time path planner for the collision-free navigation of multirotor aerial robots in dynamic environments. 2017 International Conference on Unmanned Aircraft Systems (ICUAS) 2017, 316 -325.

AMA Style

Jose Luis Sanchez-Lopez, Jesus Pestana, Pascual Campoy. A robust real-time path planner for the collision-free navigation of multirotor aerial robots in dynamic environments. 2017 International Conference on Unmanned Aircraft Systems (ICUAS). 2017; ():316-325.

Chicago/Turabian Style

Jose Luis Sanchez-Lopez; Jesus Pestana; Pascual Campoy. 2017. "A robust real-time path planner for the collision-free navigation of multirotor aerial robots in dynamic environments." 2017 International Conference on Unmanned Aircraft Systems (ICUAS) , no. : 316-325.

Article
Published: 02 May 2017 in Journal of Intelligent & Robotic Systems
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To achieve fully autonomous operation for Unmanned Aerial Systems (UAS) it is necessary to integrate multiple and heterogeneous technical solutions (e.g., control-based methods, computer vision methods, automated planning, coordination algorithms, etc.). The combination of such methods in an operational system is a technical challenge that requires efficient architectural solutions. In a robotic engineering context, where productivity is important, it is also important to minimize the effort for the development of new systems. As a response to these needs, this paper presents Aerostack, an open-source software framework for the development of aerial robotic systems. This framework facilitates the creation of UAS by providing a set of reusable components specialized in functional tasks of aerial robotics (trajectory planning, self localization, etc.) together with an integration method in a multi-layered cognitive architecture based on five layers: reactive, executive, deliberative, reflective and social. Compared to other software frameworks for UAS, Aerostack can provide higher degrees of autonomy and it is more versatile to be applied to different types of hardware (aerial platforms and sensors) and different types of missions (e.g. multi robot swarm systems). Aerostack has been validated during four years (since February 2013) by its successful use on many research projects, international competitions and public exhibitions. As a representative example of system development, this paper also presents how Aerostack was used to develop a system for a (fictional) fully autonomous indoors search and rescue mission.

ACS Style

Jose Luis Sanchez-Lopez; Martin Molina; Hriday Bavle; Carlos Sampedro; Ramón A. Suárez Fernández; Pascual Campoy. A Multi-Layered Component-Based Approach for the Development of Aerial Robotic Systems: The Aerostack Framework. Journal of Intelligent & Robotic Systems 2017, 88, 683 -709.

AMA Style

Jose Luis Sanchez-Lopez, Martin Molina, Hriday Bavle, Carlos Sampedro, Ramón A. Suárez Fernández, Pascual Campoy. A Multi-Layered Component-Based Approach for the Development of Aerial Robotic Systems: The Aerostack Framework. Journal of Intelligent & Robotic Systems. 2017; 88 (2-4):683-709.

Chicago/Turabian Style

Jose Luis Sanchez-Lopez; Martin Molina; Hriday Bavle; Carlos Sampedro; Ramón A. Suárez Fernández; Pascual Campoy. 2017. "A Multi-Layered Component-Based Approach for the Development of Aerial Robotic Systems: The Aerostack Framework." Journal of Intelligent & Robotic Systems 88, no. 2-4: 683-709.

Conference paper
Published: 01 June 2016 in 2016 International Conference on Unmanned Aircraft Systems (ICUAS)
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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.

ACS Style

Carlos Sampedro; Hriday Bavle; Jose Luis Sanchez-Lopez; Ramón A. Suárez Fernández; Alejandro Rodriguez-Ramos; Martin Molina; Pascual Campoy. A flexible and dynamic mission planning architecture for UAV swarm coordination. 2016 International Conference on Unmanned Aircraft Systems (ICUAS) 2016, 355 -363.

AMA Style

Carlos Sampedro, Hriday Bavle, Jose Luis Sanchez-Lopez, Ramón A. Suárez Fernández, Alejandro Rodriguez-Ramos, Martin Molina, Pascual Campoy. A flexible and dynamic mission planning architecture for UAV swarm coordination. 2016 International Conference on Unmanned Aircraft Systems (ICUAS). 2016; ():355-363.

Chicago/Turabian Style

Carlos Sampedro; Hriday Bavle; Jose Luis Sanchez-Lopez; Ramón A. Suárez Fernández; Alejandro Rodriguez-Ramos; Martin Molina; Pascual Campoy. 2016. "A flexible and dynamic mission planning architecture for UAV swarm coordination." 2016 International Conference on Unmanned Aircraft Systems (ICUAS) , no. : 355-363.

Conference paper
Published: 01 June 2016 in 2016 International Conference on Unmanned Aircraft Systems (ICUAS)
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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.

ACS Style

Jose Luis Sanchez-Lopez; Ramón A. Suárez Fernández; Hriday Bavle; Carlos Sampedro; Martin Molina; Jesus Pestana; Pascual Campoy. AEROSTACK: An architecture and open-source software framework for aerial robotics. 2016 International Conference on Unmanned Aircraft Systems (ICUAS) 2016, 332 -341.

AMA Style

Jose Luis Sanchez-Lopez, Ramón A. Suárez Fernández, Hriday Bavle, Carlos Sampedro, Martin Molina, Jesus Pestana, Pascual Campoy. AEROSTACK: An architecture and open-source software framework for aerial robotics. 2016 International Conference on Unmanned Aircraft Systems (ICUAS). 2016; ():332-341.

Chicago/Turabian Style

Jose Luis Sanchez-Lopez; Ramón A. Suárez Fernández; Hriday Bavle; Carlos Sampedro; Martin Molina; Jesus Pestana; Pascual Campoy. 2016. "AEROSTACK: An architecture and open-source software framework for aerial robotics." 2016 International Conference on Unmanned Aircraft Systems (ICUAS) , no. : 332-341.

Journal article
Published: 11 March 2016 in Sensors
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Autonomous route following with road vehicles has gained popularity in the last few decades. In order to provide highly automated driver assistance systems, different types and combinations of sensors have been presented in the literature. However, most of these approaches apply quite sophisticated and expensive sensors, and hence, the development of a cost-efficient solution still remains a challenging problem. This work proposes the use of a single monocular camera sensor for an automatic steering control, speed assistance for the driver and localization of the vehicle on a road. Herein, we assume that the vehicle is mainly traveling along a predefined path, such as in public transport. A computer vision approach is presented to detect a line painted on the road, which defines the path to follow. Visual markers with a special design painted on the road provide information to localize the vehicle and to assist in its speed control. Furthermore, a vision-based control system, which keeps the vehicle on the predefined path under inner-city speed constraints, is also presented. Real driving tests with a commercial car on a closed circuit finally prove the applicability of the derived approach. In these tests, the car reached a maximum speed of 48 km/h and successfully traveled a distance of 7 km without the intervention of a human driver and any interruption.

ACS Style

Miguel Angel Olivares-Mendez; Jose Luis Sanchez-Lopez; Felipe Jimenez; Pascual Campoy; Seyed Amin Sajadi-Alamdari; Holger Voos. Vision-Based Steering Control, Speed Assistance and Localization for Inner-City Vehicles. Sensors 2016, 16, 362 .

AMA Style

Miguel Angel Olivares-Mendez, Jose Luis Sanchez-Lopez, Felipe Jimenez, Pascual Campoy, Seyed Amin Sajadi-Alamdari, Holger Voos. Vision-Based Steering Control, Speed Assistance and Localization for Inner-City Vehicles. Sensors. 2016; 16 (3):362.

Chicago/Turabian Style

Miguel Angel Olivares-Mendez; Jose Luis Sanchez-Lopez; Felipe Jimenez; Pascual Campoy; Seyed Amin Sajadi-Alamdari; Holger Voos. 2016. "Vision-Based Steering Control, Speed Assistance and Localization for Inner-City Vehicles." Sensors 16, no. 3: 362.

Journal article
Published: 01 January 2016 in DYNA
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The origin and development of unmanned aviation has been almost matched that of manned aviation, starting both from an almost common point. As in conventional manned aviation, military applications, have been the motor of technological development and the potential applications of these types of systems throughout much of the twentieth century and early twenty-first century. Finally it has been in relatively recent times that these systems are experiencing an impressive boom due to the discovery of the wide variety of commercial and civil operations that are able to perform very effectively. This paper attempts to summarize the historical evolution that these systems have suffered and in the end, to present a quick analysis of the major civil / commercial applications, trying to provide an overview of the main types of systems, their classification and general configuration.Peer Reviewe

ACS Style

Cristina Cuerno Rejado; Luis Garcia Hernandez; Alejandro Sanchez Carmona; Adrian Carrio Fernandez; Jose Luis Sanchez-Lopez; Pascual Campoy Cervera. EVOLUCIÓN HISTÓRICA DE LOS VEHICULOS AEREOS NO TRIPULADOS HASTA LA ACTUALIDAD. DYNA 2016, 91, 282 -288.

AMA Style

Cristina Cuerno Rejado, Luis Garcia Hernandez, Alejandro Sanchez Carmona, Adrian Carrio Fernandez, Jose Luis Sanchez-Lopez, Pascual Campoy Cervera. EVOLUCIÓN HISTÓRICA DE LOS VEHICULOS AEREOS NO TRIPULADOS HASTA LA ACTUALIDAD. DYNA. 2016; 91 (1):282-288.

Chicago/Turabian Style

Cristina Cuerno Rejado; Luis Garcia Hernandez; Alejandro Sanchez Carmona; Adrian Carrio Fernandez; Jose Luis Sanchez-Lopez; Pascual Campoy Cervera. 2016. "EVOLUCIÓN HISTÓRICA DE LOS VEHICULOS AEREOS NO TRIPULADOS HASTA LA ACTUALIDAD." DYNA 91, no. 1: 282-288.