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Article

Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors

1
Department of Automation, Tsinghua University, Beijing 100084, China
2
National Key Laboratory on Flight Vehicle Control Integrated Technology, Flight Automatic Control Research Institute, Xi'an 710065, China
*
Author to whom correspondence should be addressed.
Academic Editor: Aboelmagd Noureldin
Micromachines 2015, 6(4), 487-522; https://doi.org/10.3390/mi6040487
Received: 27 December 2014 / Revised: 11 April 2015 / Accepted: 17 April 2015 / Published: 22 April 2015
(This article belongs to the Special Issue Next Generation MEMS-Based Navigation—Systems and Applications)
This paper presents a non-linear state observer-based integrated navigation scheme for estimating the attitude, position and velocity of micro aerial vehicles (MAV) operating in GPS-denied indoor environments, using the measurements from low-cost MEMS (micro electro-mechanical systems) inertial sensors and an RGB-D camera. A robust RGB-D visual odometry (VO) approach was developed to estimate the MAV’s relative motion by extracting and matching features captured by the RGB-D camera from the environment. The state observer of the RGB-D visual-aided inertial navigation was then designed based on the invariant observer theory for systems possessing symmetries. The motion estimates from the RGB-D VO were fused with inertial and magnetic measurements from the onboard MEMS sensors via the state observer, providing the MAV with accurate estimates of its full six degree-of-freedom states. Implementations on a quadrotor MAV and indoor flight test results demonstrate that the resulting state observer is effective in estimating the MAV’s states without relying on external navigation aids such as GPS. The properties of computational efficiency and simplicity in gain tuning make the proposed invariant observer-based navigation scheme appealing for actual MAV applications in indoor environments. View Full-Text
Keywords: integrated navigation; micro aerial vehicles (MAVs); state observer; visual odometry (VO); RGB-D cameras integrated navigation; micro aerial vehicles (MAVs); state observer; visual odometry (VO); RGB-D cameras
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MDPI and ACS Style

Li, D.; Li, Q.; Tang, L.; Yang, S.; Cheng, N.; Song, J. Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors. Micromachines 2015, 6, 487-522. https://doi.org/10.3390/mi6040487

AMA Style

Li D, Li Q, Tang L, Yang S, Cheng N, Song J. Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors. Micromachines. 2015; 6(4):487-522. https://doi.org/10.3390/mi6040487

Chicago/Turabian Style

Li, Dachuan, Qing Li, Liangwen Tang, Sheng Yang, Nong Cheng, and Jingyan Song. 2015. "Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors" Micromachines 6, no. 4: 487-522. https://doi.org/10.3390/mi6040487

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