NDLI: Invariant Extended Kalman Filter-based state estimation for MAV in GPS-denied environments

Content Provider	IEEE Xplore Digital Library
Author	Dachuan Li Qing Li Nong Cheng Sheng Yang Jingyan Song Liangwen Tang
Copyright Year	2014
Description	Author affiliation: Nat. Key Lab. on Flight Vehicle Control Integrated Technol., Flight Autom. Control Res. Inst., Xi'an, China (Liangwen Tang) \|\| Dept. of Autom., Tsinghua Univ., Beijing, China (Dachuan Li; Qing Li; Nong Cheng; Sheng Yang; Jingyan Song)
Abstract	This paper presents a RGB-D aided inertial navigation system that uses RGB-D sensor and low cost inertial measurement sensors (IMU) to provide state estimates for micro aerial vehicles (MAV) in GPS-denied indoor environments. The state estimation approach is based on the invariant observer theory which is developed for systems possessing symmetries. In our system, we review the invariant observer theory and design the invariant observer (Invariant Extended Kalman Filter, IEKF) based on the analysis of system symmetry for the RGB-D aided inertial navigation model evolving on a Lie group. In addition, a robust RGB-D based motion estimation approach is developed to provide relative pose estimates using feature correspondences captured by the RGB-D sensor. The RGB-D estimates are fused with inertial measurements through the IEKF-based observer which yields a simplified error dynamics and simplifies the calculation of gain matrices. The resulting framework is implemented and validated on a MAV, and experimental results from actual indoor flight tests demonstrate the effectiveness of the approach.
Starting Page	803
Ending Page	810
File Size	1800392
Page Count	8
File Format	PDF
ISBN	9781479930784
e-ISBN	9781479930807
DOI	10.1109/ICACCI.2014.6968244
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-24
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accelerometers Navigation Fuses Indoor navigation Kalman filter Invariant observe Micro aerial vehicles (MAVs) Micromechanical devices Q measurement Three-dimensional displays RGB-D sensor Sensors State estimation
Content Type	Text
Resource Type	Article

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