Inspection of Penstocks and Featureless Tunnel-like Environments Using Micro UAVs
Micro UAVs are receiving a great deal of attention in many diverse applications. In this paper, we are interested in a unique application, surveillance for maintenance of large infrastructure assets such as dams and penstocks, where the goal is to periodically inspect and map the structure to detect features that might indicate the potential for failures. Availability of architecture drawings of these constructions makes the mapping problem easier. However large buildings with featureless geometries pose a significant problem since it is difficult to design a robust localization algorithm for inspection operations. In this paper we show how a small quadrotor equipped with minimal sensors can be used for inspection of tunnel-like environments such as seen in dam penstocks. Penstocks in particular lack features and do not provide adequate structure for robot localization, especially along the tunnel axis. We develop a Rao-Blackwellized particle filter based localization algorithm which uses a derivative of the ICP for integrating laser measurements and IMU for short-to-medium range pose estimation. To our knowledge, this is the only study in the literature focusing on localization and autonomous control of a UAV in 3-D, featureless tunnel-like environments. We show the success of our work with results from real experiments.
KeywordsAnisotropy Covariance Transportation Tate Triad
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