In this paper, a visual inertial fusion framework is proposed for estimating the metric states of a Micro Aerial Vehicle (MAV) using optic flow (OF) and a homography model. Aided by the attitude estimation from the on-board Inertial Measurement Unit (IMU), the computed homography matrix is reshaped into a vector and directly fed into an Extend Kalman Filter (EKF). The sensor fusion method is able to recover metric distance, speed, acceleration bias and surface normal of the observed plane. We further consider reducing the size of the filter by using only part of the homography matrix as the system observation. Simulation results show that these smaller filters have reduced observability compared with the filter using the complete homography matrix, however it is still possible to estimate the metric states as long as one of the axes is linearly excited. Experiments using real sensory data show that our method is superior to the homography decomposition method for state and slope estimation. The proposed method is also validated in closed-loop flight tests of a quadrotor.
Journal of Intelligent & Robotic Systems – Springer Journals
Published: Feb 21, 2017
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera