{'fraction_non_alphanumeric': 0.011198208286674132, 'fraction_numerical': 0.0, 'mean_word_length': 5.824427480916031, '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}}
Evolutionary Path Planning for Robot Navigation Under Varying Terrain Conditions

Path planning is an essential component in the control software for an autonomous mobile robot. Evolutionary strategies are employed to determine optimal paths for their robustness and ability to solve complex problems. However, current evolutionary approaches fail to consider varying terrain conditions when determining an optimal path and offer only path planning without trajectory planning. This chapter presents an approach that determines a near optimal path while incorporating trajectory planning in the solution. Fuzzy linguistic variables are used represent the inherent imprecision and uncertainty in the terrain conditions presented to the robot. Most importantly, the method is computationally efficient and robust, providing real-time response and the ability to operate in a dynamic environment.