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Pallet detection is a critical technology for automated guided vehicles, which directly affects production efficiency. A novel pallet detection method for automated guided vehicles based on point cloud data is proposed, which consists of five modules including point cloud preprocessing, key point extraction, feature description, surface matching and point cloud registration. The proposed method combines the color with the geometric features of the pallet point cloud and constructs a new Adaptive Color Fast Point Feature Histogram (ACFPFH) feature descriptor by selecting the optimal neighborhood adaptively. In addition, a new surface matching method called the Bidirectional Nearest Neighbor Distance Ratio-Approximate Congruent Triangle Neighborhood (BNNDR-ACTN) is proposed. The proposed method overcomes the problems of current methods such as low efficiency, poor robustness, random parameter selection, and being time-consuming. To verify the performance, the proposed method is compared with the traditional and modified Iterative Closest Point (ICP) methods in two real-world cases. The results show that the Root Mean Square Error (RMSE) is reduced to 0.009 and the running time is reduced to 0.989 s, which demonstrates that the proposed method has faster registration speed while maintaining higher registration accuracy.<\/jats:p>","DOI":"10.3390\/s22208019","type":"journal-article","created":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:34:30Z","timestamp":1666312470000},"page":"8019","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A Novel Pallet Detection Method for Automated Guided Vehicles Based on Point Cloud Data"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8721-9755","authenticated-orcid":false,"given":"Yiping","family":"Shao","sequence":"first","affiliation":[{"name":"College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China"},{"name":"Noblelift Intelligent Equipment Co., Ltd., Huzhou 313100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhengshuai","family":"Fan","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baochang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Noblelift Intelligent Equipment Co., Ltd., Huzhou 313100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minlong","family":"Zhou","sequence":"additional","affiliation":[{"name":"Noblelift Intelligent Equipment Co., Ltd., Huzhou 313100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhihui","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiansha","family":"Lu","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.measurement.2016.12.037","article-title":"Raspberry Pi as a low-cost data acquisition system for human powered vehicles","volume":"100","author":"Ambroz","year":"2017","journal-title":"Measurement"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1007\/s10845-018-1459-y","article-title":"A mechanism for scheduling multi robot intelligent warehouse system face with dynamic demand","volume":"31","author":"Li","year":"2018","journal-title":"J. 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