{'fraction_non_alphanumeric': 0.02186421173762946, 'fraction_numerical': 0.0, 'mean_word_length': 5.641221374045801, '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}}
Path planning based on improved multi-objective particle swarm algorithm

This paper proposes an improved multi-objective particle swarm algorithm (MOPSO) to solve the path planning problem of mobile robots. The path planning problem is reduced to the three-objective optimization problem of constraint of path length, path smoothness, and path safety. In this paper, a multiobjective particle swarm optimization algorithm is used, so that multiple targets for path planning can be optimized simultaneously and reasonably, and a single run can provide multiple optimized candidate paths. Aiming at the common problems of multi-objective optimization algorithms, multiple fusion strategies were proposed to improve the effectiveness of the algorithm. Finally, simulation results verify the ability of the improved algorithm to generate high-quality Pareto optimal paths.