Observatorio de I+D+i UPM

Memorias de investigación
?A General Architecture For Autonomous Navigation Of Unmanned Aerial Systems?
Áreas de investigación
  • Automática
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.
Tipo de Tesis
Sobresaliente cum laude
Esta actividad pertenece a memorias de investigación
  • Director: Pascual Campoy Cervera (UPM)
  • Autor: Jose Luis Sanchez Lopez (UPM)
  • Director: Martin Molina Gonzalez (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Visión por Computador y Robótica Aérea
  • Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC
  • Departamento: Inteligencia Artificial
  • Departamento: Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial
S2i 2021 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
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