contributions:
- An improved tightly-coupled,optimization-based monocular visual-intertial state estimation framework with robust initialization,IMU bias calibration and loop closure
- Real-time implementation of state estimator and AR demo on mobile devices
- Open source release
system
systemchapter
- 1 IMU Pre-integration
- 2 LOOP DETECTION AND FEATURE RETRIEVAL
-
LOOP DETECTION
LOOP DETECTION - FEATURE RETRIEVAL
- 1 KLT tracker
-
2 BoW Vector Matches
feature retrieval
- 3 ESTIMATOR INITIALIZATION
for :metric scale (feature depth), gravity vector, body velocity, and gyroscope bias.
- Vision-Only Structure from Motion
-
Visual-Inertial Alignment(视觉和惯导对齐)
we first recover the gyroscope bias, then initialize velocity, gravity vector, and met- ric scale.
visual-inertial alignment
网友评论