{'fraction_non_alphanumeric': 0.028933092224231464, 'fraction_numerical': 0.0, 'mean_word_length': 5.224719101123595, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Combined Visual-Inertial Navigation System of MSCKF And EKF-SLAM

This paper presents a navigation architecture combining a monocular camera and inertial measurement unit (IMU). The proposed hybrid estimation framework consist of two complementary algorithms: a Multi-State Constrained Kalman Filter (MSCKF) and EKF-based SLAM. We improve the outlier curling by using two-point RANSAC method in the tracking module and one-point RANSAC method in the EKF measurement part. Experiment shows that the estimator can attain high-accuracy and robust result.