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Jose Luis Sanchez Lopez

Jose Luis Sanchez Lopez

Research associate

Fakultät oder Zentrum Interdisciplinary Centre for Security, Reliability and Trust
Forschungseinheit SnT
Postadresse Université du Luxembourg
29, avenue JF Kennedy
L-1855 Luxembourg
Büroadresse JFK Building, E04-425
E-Mail
Telefon (+352) 46 66 44 5380
Fax (+352) 46 66 44 35380

Jose-Luis Sanchez-Lopez is a post-doctoral research associate at Automation & Robotics Research Group of the Interdisciplinary Centre for Security Reliability and Trust (SnT) of the University of Luxembourg (since June 2017).

He received his Ph. D. in Robotics (May 2017), his Master degree in Automation and Robotics (Oct. 2012), and his Engineering degree in Industrial Engineering (Sep. 2010), at the Technical University of Madrid.

He was a visiting researcher during six months (Jul. – Dec. 2012) at Arizona State University (AZ, USA), and during thirteen months (Sep. – Dec. 2014 & Nov. 2015 – Oct. 2016) at LAAS-CNRS (Toulouse, France).

His main research goal is to provide robots, with a special focus on aerial robots, with the maximum level of autonomy allowing them to perform different missions without human intervention. His research interests comprise intelligent and cognitive system architectures, multi-agent systems, sensor fusion and state estimation, localization and mapping, trajectory and path planning, computer vision and machine learning. He has authored more than 35 publications related to these fields.

Last updated on: Mittwoch, den 14. März 2018

Here is my updated CV (14/03/2018)

Curriculum Vitae (pdf)



Last updated on: 14 Mär 2018

Title: A General Architecture for Autonomous Navigation of Unmanned Aerial Systems

Defense date: May 2017

Supervisors: Prof. Pascual Campoy Cervera and Prof. Martin Molina Gonzalez

University: Technical University of Madrid, Madrid (Spain)

Abstract:
Achieving a fully autonomous navigation of a fleet of aerial robots when performing complex dynamic missions in challenging unstructured environments is an essential requirement to simplify the use of micro aerial vehicles and to extend their utilization to a greater number of applications. The development of a multi-robot fully autonomous intelligent system is still an open problem with partial and incomplete solutions in aerial robotics, and only some open source architecture frameworks for aerial systems have been developed so far, which present limitations in their autonomy level and in their versatility.
This thesis presents a versatile system architecture for aerial robotics that enables the fully autonomous operation of an aerial multi-robot system and fulfills the requirements of being mission, platform, and environment agnostic. It has been characterized in an abstract and general level, defining its seven subsystems, their functionalities, and their interfaces in a top-level way that guarantees the versatility and flexibility. The seven proposed subsystems are: Feature Extraction System, Motor System, Situation Awareness System, Executive System, Planning System, Supervision System, and Communication System. This system architecture provides system designers the initial architecture for developing their own fully autonomous intelligent aerial multi-robot systems. The validation of the proposed system architecture is a complex task since the performance of the complete system is highly dependent on the mission, the environment, the hardware setup, the employed algorithms, and their software implementation. Three kinds of scenarios were successfully used to provide a global evaluation of the complete system, validating the performance of the proposed system architecture: (1) international aerial robotics competitions, (2) self-proposed challenges, and (3) public demonstrations.
In addition, this thesis presents several algorithms, with different level of detail, that yield to an increased level of autonomy of the aerial robotic systems, developed in the context of particular applications. These algorithms can be gathered in the following five groups: (1) perception, (2) control, (3) planning and task execution, (4) intelligence and cognition, and (5) communication and interaction. All these components have been evaluated isolatedly, demonstrating their individual performance. Nevertheless, their importance stands out when integrated into the complete system. The most important components presented in this thesis, analyzed with a high level of detail, are the following: (1) helipad detection and reconstruction for shipboard landing, (2) perception based on odometry and visual markers with environment reconstruction, (3) perception based on odometry and computer vision for gridded maps, (4) perception based on multi-sensor fusion with environment reconstruction, and (5) collision-free path planning for dynamic environments.
This thesis presents as well, an open-source software framework, called Aerostack, that facilitates a cost and time effective implementation of the designed system architecture and the developed algorithms by means of software components. This framework is modularly organized in software packages gathered by their functionality, their dependencies, and their life state. The proposed software framework relies on the widely used ROS middleware for interprocess communication and uses an asynchronous multiprocess paradigm where every elementary functionality is implemented as a single process, easing the development and allowing a distributed processing. The proposed software framework has demonstrated to be versatile and scalable, being the developers capable of reusing its software modules as needed, and modifying or developing new modules without adaptations of any other components.

Download: PhD thesis (pdf)



Last updated on: 14 Mär 2018

You can find my open-source software in:



Last updated on: 14 Mär 2018

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2018

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See detailFast and Robust Flight Altitude Estimation of Multirotor UAVs in Dynamic Unstructured Environments Using 3D Point Cloud Sensors
Bavle, Hriday; Sanchez Lopez, Jose Luis; de la Puente, Paloma; Rodriguez-Ramos, Alejandro; Sampedro, Carlos; Campoy, Pascual

in Aerospace (2018), 5(3),

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See detailModel Predictive Control for Aerial Collision Avoidance in Dynamic Environments
Castillo Lopez, Manuel; Sajadi Alamdari, Seyed Amin; Sanchez Lopez, Jose Luis; Olivares Mendez, Miguel Angel; Voos, Holger

in 26th Mediterranean Conference on Control and Automation (MED), Zadar, Croatia, 19-22 June 2018 (2018, June)

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See detailTowards trajectory planning from a given path for multirotor aerial robots trajectory tracking
Sanchez Lopez, Jose Luis; Olivares Mendez, Miguel Angel; Castillo Lopez, Manuel; Voos, Holger

in 2018 International Conference on Unmanned Aircraft Systems (ICUAS), Dallas 12-15 June 2018 (2018, June)

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See detailA Real-Time 3D Path Planning Solution for Collision-Free Navigation of Multirotor Aerial Robots in Dynamic Environments
Sanchez Lopez, Jose Luis; Wang, Min; Olivares Mendez, Miguel Angel; Molina, Martin; Voos, Holger

in Journal of Intelligent and Robotic Systems (2018)

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2017

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See detailHuman-Robot Cooperation in Surface Inspection Aerial Missions
Molina, Martin; Frau, Pedro; Maraval, Dario; Sanchez Lopez, Jose Luis; Bavle, Hriday; Campoy, Pascual

in 2017 International Micro Air Vehicle Conference and Flight Competition (IMAV), Toulouse, France, 18-21 Septembre 2017 (2017, September 21)

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