Observatorio de I+D+i UPM

Memorias de investigación
"Detection and Tracking of Dynamic Objects. A MultiRobot Approach to Critical Infrastructures Surveillance"
Áreas de investigación
  • Automática
Critical Infrastructures (CIs) security and surveillance are a growing concern for many countries and companies. However, Multi Robot System (MRS) have not been yet broadly used in this type of facilities. This dissertation presents a novel study of the challenges presented by this situation and proposes solutions to this specific problem. First, a comprehensive analysis of different types of CI has been carried out, putting much emphasis in the influence of the different characteristics of the facilities in the design of a security and surveillance MRS. One of the most important aspects of the surveillance of a CI is the detection of intruders. From a technical point of view this problem can be abstracted as equivalent to the Detection and Tracking of Mobile Objects (DATMO). This dissertation proposes algorithms to solve this specific problem in a CI environment. Using 3D range images of the environment as input data, two detection algorithms for ground robots have been developed. These detection algorithms provide a list of moving objects in the robot detection area. Direct image differentiation and computer vision techniques are used when the robot is static. Multi-layer ground reconstructions are compared to detect the dynamic objects when the robot is moving. Since CIs have usually a large extension, it is very useful to be able to include aerial vehicles in the surveillance MRS. Therefore, a moving object detection algorithm for aerial vehicles has been also developed. This algorithm compares the real optical flow obtained from a down-face oriented camera with an artificial optical flow computed using a RANSAC based homography matrix. Two tracking algorithms have been developed to follow the moving objects trajectories. These algorithms can efficiently handle occlusions and crossings, as well as exchange information among robots. The multirobot tracking can be applied to any type of communication structure: centralized, decentralized or a combination of both. Even more, the developed tracking algorithms are independent of the detection algorithms and could be potentially used with other detection procedures or even with static sensors, such as cameras. Moreover, using the 3D point clouds available to the robots, a relative localization algorithm has been developed that allows the robot to improve their position estimation with observations from other robots has been developed. All the developed algorithms have been extensively tested in different simulated CIs using the Webots robotics simulator. Furthermore, the algorithms have also been validated with real robots. In conclusion, this dissertation presents a multirobot approach to Critical Infrastructure Surveillance, mainly focusing on Detecting and Tracking Dynamic Objects. in proportion compared to its biological counterpart Cynopterus brachyotis, which provides the biological foundations for developing accurate mathematical models and methods that allow for mimicking bat flight
Tipo de Tesis
Esta actividad pertenece a memorias de investigación
  • Director: Antonio Barrientos Cruz (UPM)
  • Director: Jaime del Cerro Giner (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Robótica y Cibernética
  • Departamento: Automática, Ingeniería Electrónica e Informática Industrial
  • Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC
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