Autonomous robotic system for tunnel structural inspection and assessment Articles uri icon

authors

  • LOUPOS, KONSTANTINOS
  • Doulamis, Anastasios D
  • STENTOUMIS, CHRISTOS
  • Protopapadakis, Eftychios
  • Makantasis, Konstantinos
  • Doulamis, Nikolaos D.
  • AMDITIS, ANGELOS
  • GONZALEZ VICTORES, JUAN CARLOS
  • MONTERO PEREZ, ROBERTO
  • MENENDEZ SALVADOR, ELISABETH
  • BALAGUER BERNALDO DE QUIROS, CARLOS
  • CHROBOCINSKI, PHILIPPE
  • LOPEZ, RAFA
  • Cantero, Miquel
  • Navarro, Roman
  • RONCAGLIA, ALBERTO
  • Belsito, Luca
  • CAMARINOPOULOS, STEPHANOS
  • Komodakis, Nikolaos
  • Singh, Praveer

publication date

  • March 2018

start page

  • 43

end page

  • 66

issue

  • 1

volume

  • 2

International Standard Serial Number (ISSN)

  • 2366-5971

Electronic International Standard Serial Number (EISSN)

  • 2366-598X

abstract

  • This paper presents a robotic platform, capable of autonomous tunnel inspection, developed under ROBO-SPECT European union funded research project. The robotic vehicle consists of a robotized production boom lift, a high precision robotic arm, advanced computer vision systems, a 3D laser scanner and an ultrasonic sensor. The autonomous inspection of tunnels requires advanced capabilities of the robotic vehicle and the computer vision sub-system. The robot localization in underground spaces and on long linear paths is a challenging task, as well as the mm accurate positioning of a robotic tip installed on a five-ton crane vehicle. Moreover, the 2D and 3D vision tasks, which support the inspection process, should tackle with poor and variable lighting conditions, low textured lining surfaces and the need for high accuracy. This contribution describes the final robotic vehicle and the developments as designed for concrete lining tunnel inspection. Results from the validation and benchmarking of the system are also included following the final tests at the operating Egnatia Motorway tunnels in northern Greece.

keywords

  • Autonomous robot; Tunnel inspection; Structural assessment; Computer vision system; Autonomous navigation; Ultrasonic sensors