Mini-UAV altitude estimation using an inertially stabilized payload

1999 ◽  
Vol 35 (4) ◽  
pp. 1191-1203 ◽  
Author(s):  
Y. Oshman ◽  
M. Isakow
Keyword(s):  
Aerospace ◽  
2018 ◽  
Vol 5 (3) ◽  
pp. 94 ◽  
Author(s):  
Hriday Bavle ◽  
Jose Sanchez-Lopez ◽  
Paloma Puente ◽  
Alejandro Rodriguez-Ramos ◽  
Carlos Sampedro ◽  
...  

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.


2017 ◽  
Vol 60 (3) ◽  
pp. 382-400 ◽  
Author(s):  
Rémi Boutteau ◽  
Peter Sturm ◽  
Pascal Vasseur ◽  
Cédric Demonceaux

2016 ◽  
Vol 16 (4) ◽  
pp. 2299-2308 ◽  
Author(s):  
Chris M. Hall ◽  
Silje E. Holmen ◽  
Chris E. Meek ◽  
Alan H. Manson ◽  
Satonori Nozawa

Abstract. The turbopause is the demarcation between atmospheric mixing by turbulence (below) and molecular diffusion (above). When studying concentrations of trace species in the atmosphere, and particularly long-term change, it may be important to understand processes present, together with their temporal evolution that may be responsible for redistribution of atmospheric constituents. The general region of transition between turbulent and molecular mixing coincides with the base of the ionosphere, the lower region in which molecular oxygen is dissociated, and, at high latitude in summer, the coldest part of the whole atmosphere. This study updates previous reports of turbopause altitude, extending the time series by half a decade, and thus shedding new light on the nature of change over solar-cycle timescales. Assuming there is no trend in temperature, at 70° N there is evidence for a summer trend of  ∼  1.6 km decade−1, but for winter and at 52° N there is no significant evidence for change at all. If the temperature at 90 km is estimated using meteor trail data, it is possible to estimate a cooling rate, which, if applied to the turbopause altitude estimation, fails to alter the trend significantly irrespective of season. The observed increase in turbopause height supports a hypothesis of corresponding negative trends in atomic oxygen density, [O]. This supports independent studies of atomic oxygen density, [O], using mid-latitude time series dating from 1975, which show negative trends since 2002.


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