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The optimized A* algorithm was compared with the original A* algorithm and the Q-learning algorithm through simulation experiments on a grid map using the MATLAB platform. The experimental results show that compared with the standard A* algorithm, the optimized A* algorithm reduces the path-planning time by 37.2% and the energy consumption by 29.5%. In addition, compared with the Q-learning algorithm, this algorithm\u2019s overall search efficiency is improved by 76.8%. Simulation results show that the optimized A* algorithm is more efficient in searching and has a shorter seek time, fully saving energy. <\/jats:p>","DOI":"10.1142\/s1793962325500370","type":"journal-article","created":{"date-parts":[[2025,3,22]],"date-time":"2025-03-22T04:29:35Z","timestamp":1742617775000},"source":"Crossref","is-referenced-by-count":0,"title":["Research on optimization A* algorithm based on energy consumption of mobile navigation robot"],"prefix":"10.1142","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1860-6401","authenticated-orcid":false,"given":"Bin","family":"Hong","sequence":"first","affiliation":[{"name":"Vehicle Intelligence and Simulation Engineering Laboratory, Internal Combustion Engine Research Institute, Tianjin University, Tianjin 300072, P. R. China"},{"name":"School of Mechanical Engineering, Tianjin University, Tianjin 300072, P. R. China"},{"name":"Tianjin Tianbo Science and Technology Co., Ltd., Tianjin 300072, P. R. 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