Fast and Robust Flight Altitude Estimation of Multirotor UAVs in Dynamic Unstructured Environments Using 3D Point Cloud Sensors

Abstract

This paper presents a fast and robust approach for estimating the flight altitude of multirotor Unmanned Aerial Vehicles (UAVs) using 3D point cloud sensors in cluttered, unstructured, and dynamic indoor environments. The objective is to present a flight altitude estimation algorithm, replacing the conventional sensors such as laser altimeters, barometers, or accelerometers, which have several limitations when used individually. Our proposed algorithm includes two stages: in the first stage, a fast clustering of the measured 3D point cloud data is performed, along with the segmentation of the clustered data into horizontal planes. In the second stage, these segmented horizontal planes are mapped based on the vertical distance with respect to the point cloud sensor frame of reference, in order to provide a robust flight altitude estimation even in presence of several static as well as dynamic ground obstacles. We validate our approach using the IROS 2011 Kinect dataset available in the literature, estimating the altitude of the RGB-D camera using the provided 3D point clouds. We further validate our approach using a point cloud sensor on board a UAV, by means of several autonomous real flights, closing its altitude control loop using the flight altitude estimated by our proposed method, in presence of several different static as well as dynamic ground obstacles. In addition, the implementation of our approach has been integrated in our open-source software framework for aerial robotics called Aerostack.

VPS-SLAM: Visual Planar Semantic SLAM for Aerial Robotic Systems

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UAV-Based Structural Damage Mapping: A Review

“…There has been a surge in research on UAV-based indoor mapping, both with single platforms and swarms. Most make use of visual SLAM to map their GPS-denied environment (e.g., [86,87]), or focusing on continuity mapping when transiting between outdoor and indoor places [88]. Others have experimented with localizing via sensors such as ultrasound [89], and the works cited in 4.2 on autonomous navigation and mapping are also relevant here.…”

Uav-Based Structural Damage Mapping – Results From 6 Years Of Research in Two European Projects

“…(iv) in recent years there has been a surge in research on UAV-based indoor mapping, both with single platforms and swarms. Most make use of visual SLAM to map their GPS-denied environment (e.g., Bavle et al 2018, Trujillo et al 2018, or focusing on continuity mapping when transiting between outdoor and indoor places (Zhang et al 2015). Others have experimented with localizing via sensors such as ultrasound (Paredes et al 2018).…”