{'fraction_non_alphanumeric': 0.020718232044198894, 'fraction_numerical': 0.0013812154696132596, 'mean_word_length': 5.25, '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 Multisensor-based Tightly Coupled Integrated Navigation System*

We present a tightly coupled multi-sensor integrated navigation and localization system based on graph optimization. To be specific, we calculate the preintegrated IMU factor by retraction strategy and use the reprojection error of the stereo camera as the visual landmark factor. Then we demonstrate their fusion with 3D line and plane primitives in the Lidar point cloud in a graph-based optimization framework. Furthermore, a segmented optimization algorithm is designed in the system and the widely used GPS and closure loop are added as constraints. The resulting visual-inertial-Lidar-GPS fusion navigation system is validated on a real-world dataset.