VINS-MKF: A Tightly-Coupled Multi-Keyframe Visual-Inertial Odometry for Accurate and Robust State Estimation.
Chaofan ZhangYong LiuFan WangYingwei XiaWen ZhangPublished in: Sensors (2018)
Keyphrases
- tightly coupled
- state estimation
- kalman filter
- inertial sensors
- fine grained
- sequential importance sampling
- computationally efficient
- extended kalman filter
- general purpose
- particle filter
- loosely coupled
- kalman filtering
- state space model
- high level
- particle filtering
- dynamic systems
- visual tracking
- dynamic model
- sensor fusion
- low level
- position and orientation
- video frames
- visual features
- multi agent
- feature extraction
- image segmentation