NDLI: Combined RGBD-inertial based state estimation for MAV in GPS-denied indoor environments

Content Provider	IEEE Xplore Digital Library
Author	Dachuan Li Qing Li Nong Cheng Qinfan Wu Jingyan Song Liangwen Tang
Copyright Year	2013
Description	Author affiliation: Sci. & Technol. on Aircraft Control Lab., Flight Autom. Control Res. Inst., Xian, China (Liangwen Tang) \|\| Dept. of Autom., Tsinghua Univ., Beijing, China (Dachuan Li; Qing Li; Nong Cheng; Qinfan Wu; Jingyan Song)
Abstract	This paper presents a integrated navigation approach for state estimation of a micro aerial vehicle (MAV) that is capable of autonomous flight in GPS-denied, indoor environments. The solution combines RGB-D sensor and inertial sensors in a tight-coupling navigation manner. Motion estimates from RGB-D visual odometry and inertial measurements are fused using an improved Extended Kalman Filter-based fusion algorithm to provide an accurate estimate of the relative position, velocity and attitude. Instead of using a global reference frame, a view-based map is employed and the algorithm maintains the position and heading relative to the current map node in the fusion algorithm. In addition, a closed-form covariance is developed to qualify the uncertainty of the RGBD visual odometry measurements, which is utilized for state update of the navigation filter. Our approach allows efficient measurement updates and enables the incorporation of RGBD visual odometry uncertainty. Experimental results of a quadrotor MAV flying in a GPS-denied indoor environment demonstrate the performance of the proposed approach. Comparisons of state estimates with ground truth measurements are also provided.
Starting Page	1
Ending Page	8
File Size	1460364
Page Count	8
File Format	PDF
ISBN	9781467357678
e-ISBN	9781467357692
DOI	10.1109/ASCC.2013.6606361
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-23
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Visualization Three-dimensional displays Navigation Motion estimation RGB-D sensor Feature extraction Robustness visual odometry micro aerial vehicle RGBD-IMU data fusion State estimation
Content Type	Text
Resource Type	Article

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