1-Point-based Monocular Motion Estimation for Computationally-Limited Micro Aerial Vehicles

Chiara Troiani (1) , Agostino Martinelli (1) , Christian Laugier (1) , Davide Scaramuzza (2)

1 E-MOTION - Geometry and Probability for Motion and Action
2 Robotics and perception group [Zurich]

We propose a novel method to estimate the relative motion between two consecutive camera views, which only requires the observation of a single feature in the scene and the knowledge of the angular rates from an inertial measurement unit, under the assumption that the local camera motion lies in a plane perpendicular to the gravity vector. Using this 1- point motion parametrization, we provide two very efficient algorithms to remove the outliers of the feature-matching process. Thanks to their inherent efficiency, the proposed algorithms are very suitable for computationally-limited robots. We test the proposed approaches on both synthetic and real data, using video footage from a small flying quadrotor. We show that our methods outperform standard RANSAC-based implementations by up to two orders of magnitude in speed, while being able to identify the majority of the inliers.

Domaines: Robotique [cs.RO]

Chiara Troiani, Agostino Martinelli, Christian Laugier, Davide Scaramuzza. 1-Point-based Monocular Motion Estimation for Computationally-Limited Micro Aerial Vehicles. 6th European Conference on Mobile Robots, Sep 2013, Barcelona, Spain. ⟨hal-00909626⟩