Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Real-time implementation of airborne inertial-SLAM
Robotics and Autonomous Systems
MonoSLAM: Real-Time Single Camera SLAM
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vision-Based Odometry and SLAM for Medium and High Altitude Flying UAVs
Journal of Intelligent and Robotic Systems
Journal of Intelligent and Robotic Systems
Journal of Intelligent and Robotic Systems
Monocular vision SLAM for indoor aerial vehicles
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Fusion of IMU and Vision for Absolute Scale Estimation in Monocular SLAM
Journal of Intelligent and Robotic Systems
Monocular-SLAM–based navigation for autonomous micro helicopters in GPS-denied environments
Journal of Field Robotics
Convergence and Consistency Analysis for Extended Kalman Filter Based SLAM
IEEE Transactions on Robotics
Inverse Depth Parametrization for Monocular SLAM
IEEE Transactions on Robotics
Rotation estimation for mobile robot based on single-axis gyroscope and monocular camera
International Journal of Automation and Computing
Hi-index | 0.00 |
This paper presents a hierarchical simultaneous localization and mapping (SLAM) system for a small unmanned aerial vehicle (UAV) using the output of an inertial measurement unit (IMU) and the bearing-only observations from an onboard monocular camera. A homography based approach is used to calculate the motion of the vehicle in 6 degrees of freedom by image feature match. This visual measurement is fused with the inertial outputs by an indirect extended Kalman filter (EKF) for attitude and velocity estimation. Then, another EKF is employed to estimate the position of the vehicle and the locations of the features in the map. Both simulations and experiments are carried out to test the performance of the proposed system. The result of the comparison with the referential global positioning system/inertial navigation system (GPS/INS) navigation indicates that the proposed SLAM can provide reliable and stable state estimation for small UAVs in GPS-denied environments.