Václav Pritzl presents Adaptive estimation of UAV altitude in complex indoor environments using degraded and time-delayed m

A novel approach for robust Unmanned Aerial Vehicle (UAV) altitude estimation
relying on laser measurements that is designed for use in complex indoor
environments is proposed in this paper. Specifically, we aim to design a system
with general usability inside multi-floor buildings. The multi-floor buildings
are characterized by areas lacking distinct vertical geometric features to be
used as reference by 3D Light Detection and Ranging (LiDAR) localization
algorithms, and by areas with either flat floors or limited areas with
inconsistent ground elevation. The proposed approach solves the problem of
adaptive fusion of data from multiple sources with apriori-unknown confidence
dependent on the current environmental properties. Whenever the environment
contains enough geometric structure, altitude data from a 3D LiDAR-based
Simultaneous Localization and Mapping (SLAM) algorithm are utilized. In
environments that are too symmetrical for reliable SLAM operation, the approach
relies mostly on measurements from a downward-facing 1D laser rangefinder,
while simultaneously detecting inconsistent ground elevation areas. These
measurements are fused with barometer data, Inertial Measurement Unit (IMU)
data, and information from the UAV position controllers. Furthermore, our
approach correctly handles the measurement delay caused by 3D LiDAR data
processing that significantly differs from other sensor delays. The performance
of the proposed approach has been validated in complex simulations and
real-world experiments with the produced altitude estimate utilized in the
control loop of the UAV.
The proposed approach is released as open-source as part of the MRS UAV System.

https://v3s.cvut.cz/results/detail/361942
Publikováno v časopise Robotics and Autonomous Systems (Q2, 2021 IF 3,7).