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This paper proposed a path planner based on the visibility graph (v-graph) for the mobile robot that uses sparse methods to speed up and simplify the construction of the v-graph. Firstly, the complementary grid framework is designed to reduce graph updating iteration costs during the data collection process in each data frame. Secondly, a filter approach based on the edge length and the number of vertices of the obstacle contour is proposed to reduce redundant nodes and edges in the v-graph. Thirdly, a bidirectional breadth-first search is combined into the path searching process in the proposed fast path planner algorithm in order to reduce the waste of exploring space. Finally, the simulation results indicate that the proposed sparse v-graph planner can significantly improve the efficiency of building the v-graph and reduce the time of path search. In highly convoluted unknown or partially known environments, our method is 40% faster than the FAR Planner and produces paths 25% shorter than it. Moreover, the physical experiment shows that the proposed path planner is faster than the FAR Planner in both the v-graph update process and laser process. The method proposed in this paper performs faster when seeking paths than the conventional method based on the occupancy grid.<\/jats:p>","DOI":"10.3390\/rs14153720","type":"journal-article","created":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T23:33:01Z","timestamp":1659569581000},"page":"3720","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["FPS: Fast Path Planner Algorithm Based on Sparse Visibility Graph and Bidirectional Breadth-First Search"],"prefix":"10.3390","volume":"14","author":[{"given":"Qunzhao","family":"Li","sequence":"first","affiliation":[{"name":"School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5426-8390","authenticated-orcid":false,"given":"Fei","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3677-1109","authenticated-orcid":false,"given":"Bing","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiquan","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xixiang","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Instrument Science & Engineering, Southeast University, Nanjing 210096, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongbo","family":"Suo","sequence":"additional","affiliation":[{"name":"Nanjing Zhongke Raycham Laser Technology Co., Ltd., Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Hess, W., Kohler, D., Rapp, H., and Andor, D. 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