{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T22:09:53Z","timestamp":1775772593763,"version":"3.50.1"},"reference-count":58,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T00:00:00Z","timestamp":1653004800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52075306"],"award-info":[{"award-number":["52075306"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>In order to obtain the optimal perspectives of the recognition target, this paper combines the motion path of the manipulator arm and camera. A path planning method to find the optimal perspectives based on an A* algorithm is proposed. The quality of perspectives is represented by means of multi-view recognition. A binary multi-view 2D kernel principal component analysis network (BM2DKPCANet) is built to extract features. The multi-view angles classifier based on BM2DKPCANet + Softmax is established, which outputs category posterior probability to represent the perspective recognition performance function. The path planning problem is transformed into a multi-objective optimization problem by taking the optimal view recognition and the shortest path distance as the objective functions. In order to reduce the calculation, the multi-objective optimization problem is transformed into a single optimization problem by fusing the objective functions based on the established perspective observation directed graph model. An A* algorithm is used to solve the single source shortest path problem of the fused directed graph. The path planning experiments with different numbers of view angles and different starting points demonstrate that the method can guide the camera to reach the viewpoint with higher recognition accuracy and complete the optimal observation path planning.<\/jats:p>","DOI":"10.3390\/a15050171","type":"journal-article","created":{"date-parts":[[2022,5,20]],"date-time":"2022-05-20T13:56:12Z","timestamp":1653054972000},"page":"171","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Research on an Optimal Path Planning Method Based on A* Algorithm for Multi-View Recognition"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7688-3311","authenticated-orcid":false,"given":"Xinning","family":"Li","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qun","family":"He","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qin","family":"Yang","sequence":"additional","affiliation":[{"name":"Shandong Bochuang Machinery Technology Co., Ltd., Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hu","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianhai","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1111\/j.1467-8659.2009.01412.x","article-title":"Learning good views through intelligent galleries","volume":"28","author":"Vieira","year":"2009","journal-title":"Comput. 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