{'fraction_non_alphanumeric': 0.015789473684210527, 'fraction_numerical': 0.0, 'mean_word_length': 5.010526315789473, '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 Line-Based Approach to SLAM Using Monocular Vision

This work purposes a line-based approach to the SLAM problem using planar information. The solution presented is based on Extended Kalman Filter, in Hough transform and in use of a homographic matrix to perform the image-world mapping . The proposed model allows the use of line features directly in the Kalman equations without additional intermediate calculations and startup delayed initialization, same images being obtained from a single camera. Results with a real robot are presented to validate the proposal.