Micro air vehicle local pose estimation with a two-dimensional laser scanner: A case study for electric tower inspection. Issue 2 (June 2018)

• Record Type: Journal Article
• Authors: Viña, Carlos; Morin, Pascal
• Other Names: Marzat Julien guest-editor.; de Croon Guido guest-editor.; Fraundorfer Friedrich guest-editor.; Morin Pascal guest-editor.; Tsourdos Antonios guest-editor.
• Is Part Of: International journal of micro air vehicles. Volume 10:Issue 2(2018)
• Page Start: 127
• Page End: 156
• Publication Date: 2018-06
• Subjects: Micro air vehicle -- airborne laser scanning -- two-dimensional light detection and ranging -- barometer -- inertial measurement unit -- iterative closest point -- state estimation; Aerosonde (Drone aircraft) -- Periodicals; Aerospace engineering -- Periodicals; Aerosonde (Drone aircraft); Aerospace engineering; Periodicals; 623.746905
• DOI: 10.1177/1756829317745316
• Languages: English
• ISSNs: 1756-8293

Abstract

Automation of inspection tasks is crucial for the development of the power industry, where micro air vehicles have shown a great potential. Self-localization in this context remains a key issue and is the main subject of this work. This article presents a methodology to obtain complete three-dimensional local pose estimates in electric tower inspection tasks with micro air vehicles, using an on-board sensor set-up consisting of a two-dimensional light detection and ranging, a barometer sensor and an inertial measurement unit. First, we present a method to track the tower's cross-sections in the laser scans and give insights on how this can be used to model electric towers. Then, we show how the popular iterative closest point algorithm, that is typically limited to indoor navigation, can be adapted to this scenario and propose two different implementations to retrieve pose information. This is complemented with attitude estimates from the inertial measurement unit measurements, based on a gain-scheduled non-linear observer formulation. An altitude observer to compensate for barometer drift is also presented. Finally, we address velocity estimation with views to feedback position control. Validations based on simulations and experimental data are presented.