{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T10:11:04Z","timestamp":1780567864344,"version":"3.54.1"},"reference-count":36,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,6,8]],"date-time":"2022-06-08T00:00:00Z","timestamp":1654646400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The Jump Point Search (JPS) algorithm ignores the possibility of any-angle walking, so the paths found by the JPS algorithm under the discrete grid map still have a gap with the real paths. To address the above problems, this paper improves the path optimization strategy of the JPS algorithm by combining the viewable angle of the Angle-Propagation Theta* (AP Theta*) algorithm, and it proposes the AP-JPS algorithm based on an any-angle pathfinding strategy. First, based on the JPS algorithm, this paper proposes a vision triangle judgment method to optimize the generated path by selecting the successor search point. Secondly, the idea of the node viewable angle in the AP Theta* algorithm is introduced to modify the line of sight (LOS) reachability detection between two nodes. Finally, the paths are optimized using a seventh-order polynomial based on minimum snap, so that the AP-JPS algorithm generates paths that better match the actual robot motion. The feasibility and effectiveness of this method are proved by simulation experiments and comparison with other algorithms. The results show that the path planning algorithm in this paper obtains paths with good smoothness in environments with different obstacle densities and different map sizes. In the algorithm comparison experiments, it can be seen that the AP-JPS algorithm reduces the path by 1.61\u20134.68% and the total turning angle of the path by 58.71\u201384.67% compared with the JPS algorithm. The AP-JPS algorithm reduces the computing time by 98.59\u201399.22% compared with the AP-Theta* algorithm.<\/jats:p>","DOI":"10.3390\/a15060198","type":"journal-article","created":{"date-parts":[[2022,6,9]],"date-time":"2022-06-09T09:59:38Z","timestamp":1654768778000},"page":"198","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Improved JPS Path Optimization for Mobile Robots Based on Angle-Propagation Theta* Algorithm"],"prefix":"10.3390","volume":"15","author":[{"given":"Yuan","family":"Luo","sequence":"first","affiliation":[{"name":"Key Laboratory of Optoelectronic Information Sensing and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiakai","family":"Lu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Optoelectronic Information Sensing and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiong","family":"Qin","sequence":"additional","affiliation":[{"name":"Key Laboratory of Optoelectronic Information Sensing and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanyu","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Optoelectronic Information Sensing and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,8]]},"reference":[{"key":"ref_1","first-page":"1107","article-title":"Path planning for a new mine rescue robot base on visual tangent graphs","volume":"41","author":"Liu","year":"2011","journal-title":"Jilin Daxue Xuebao"},{"key":"ref_2","first-page":"14","article-title":"Research and Experiment on Recognition and Location System for Citrus Picking Robot in Natural Environment","volume":"50","author":"Yang","year":"2019","journal-title":"Nongye Jixie Xuebao"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"718","DOI":"10.1109\/TIE.2004.825197","article-title":"Complete coverage navigation of cleaning robots using triangular-cell-based map","volume":"51","author":"Oh","year":"2004","journal-title":"IEEE Trans. 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