Navigation Aiding by a Hybrid Laser-Camera Motion Estimator for Micro Aerial Vehicles
AbstractMicro Air Vehicles (MAVs) equipped with various sensors are able to carry out autonomous flights. However, the self-localization of autonomous agents is mostly dependent on Global Navigation Satellite Systems (GNSS). In order to provide an accurate navigation solution in absence of GNSS signals, this article presents a hybrid sensor. The hybrid sensor is a deep integration of a monocular camera and a 2D laser rangefinder so that the motion of the MAV is estimated. This realization is expected to be more flexible in terms of environments compared to laser-scan-matching approaches. The estimated ego-motion is then integrated in the MAV’s navigation system. However, first, the knowledge about the pose between both sensors is obtained by proposing an improved calibration method. For both calibration and ego-motion estimation, 3D-to-2D correspondences are used and the Perspective-3-Point (P3P) problem is solved. Moreover, the covariance estimation of the relative motion is presented. The experiments show very accurate calibration and navigation results. View Full-Text
Share & Cite This Article
Atman, J.; Popp, M.; Ruppelt, J.; Trommer, G.F. Navigation Aiding by a Hybrid Laser-Camera Motion Estimator for Micro Aerial Vehicles. Sensors 2016, 16, 1516.
Atman J, Popp M, Ruppelt J, Trommer GF. Navigation Aiding by a Hybrid Laser-Camera Motion Estimator for Micro Aerial Vehicles. Sensors. 2016; 16(9):1516.Chicago/Turabian Style
Atman, Jamal; Popp, Manuel; Ruppelt, Jan; Trommer, Gert F. 2016. "Navigation Aiding by a Hybrid Laser-Camera Motion Estimator for Micro Aerial Vehicles." Sensors 16, no. 9: 1516.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.