{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T06:30:55Z","timestamp":1782369055128,"version":"3.54.5"},"reference-count":22,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T00:00:00Z","timestamp":1698364800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Industry-university-research Collaborative Innovation Fund project","award":["2020-CXY26"],"award-info":[{"award-number":["2020-CXY26"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Linear conveyors, traditional tools for cargo transportation, have faced criticism due to their directional constraints, inability to adjust poses, and single-item conveyance, making them unsuitable for modern flexible logistics demands. This paper introduces a platform designed to convey and adjust cargo boxes according to their spatial positions and orientations. Additionally, a cargo pose recognition algorithm that integrates image and point cloud data are presented. By aligning depth camera data, the axis-aligned bounding box (AABB) point serves as the image\u2019s region of interest (ROI). Peaks extracted from the image\u2019s Hough transform are refined using RANSAC-based point cloud linear fitting, then integrated with the point cloud\u2019s oriented bounding box (OBB). Notably, the algorithm eliminates the need for deep learning and registration, enabling its use in rectangular cargo boxes of various sizes. A comparative experiment using accelerometer sensors for pose acquisition revealed a deviation of &lt;0.7\u00b0 between the two processes. Throughout the real-time adjustments controlled by the experimental platform, cargo angles consistently remained stable. The proposed two-dimensional conveyance platform, compared to existing methods, exhibits simplicity, accurate recognition, enhanced flexibility, and wide applicability.<\/jats:p>","DOI":"10.3390\/s23218754","type":"journal-article","created":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T11:50:18Z","timestamp":1698407418000},"page":"8754","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Design of a Two-Dimensional Conveyor Platform with Cargo Pose Recognition and Adjustment Capabilities"],"prefix":"10.3390","volume":"23","author":[{"given":"Zhiguo","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Information and Automation Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information and Automation Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information and Automation Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3649-3113","authenticated-orcid":false,"given":"Fengying","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Information and Automation Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shijie","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Information and Automation Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Information and Automation Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linhan","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Information and Automation Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Bajda, M., and Hardygora, M. (2021). Analysis of the Influence of the Type of Belt on the Energy Consumption of Transport Processes in a Belt Conveyor. Energies, 14.","DOI":"10.3390\/en14196180"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"621","DOI":"10.4236\/ojbm.2016.44063","article-title":"Research on Green Express Packaging Design under the Electronic Commerce","volume":"4","author":"Wang","year":"2016","journal-title":"Open J. Bus. Manag."},{"key":"ref_3","first-page":"37","article-title":"Intelligent sorting machine design applied to express industry","volume":"6","author":"Li","year":"2020","journal-title":"Int. Core J. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"104976","DOI":"10.1016\/j.engappai.2022.104976","article-title":"Optimal scheduling for palletizing task using robotic arm and artificial bee colony algorithm","volume":"113","author":"Szczepanski","year":"2022","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/j.procir.2019.02.117","article-title":"Control strategies for small-scaled conveyor modules enabling highly flexible material flow systems","volume":"79","author":"Uriarte","year":"2019","journal-title":"Procedia CIRP"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.1016\/j.procir.2021.11.180","article-title":"Study on conflict-free AGVs path planning strategy for workshop material distribution systems","volume":"104","author":"Liyun","year":"2021","journal-title":"Procedia CIRP"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"055083","DOI":"10.1088\/1757-899X\/688\/5\/055083","article-title":"Model and algorithm for co-scheduling of stackers and single RGV during retrieval process in AS\/RS","volume":"688","author":"Hu","year":"2019","journal-title":"IOP Conf. Ser. Mater. Sci. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Holzer, S., Hinterstoisser, S., Ilic, S., and Navab, N. (2009, January 20\u201325). Distance transform templates for object detection and pose estimation. Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, USA.","DOI":"10.1109\/CVPR.2009.5206777"},{"key":"ref_9","unstructured":"Hinterstoisser, S., Lepetit, V., Ilic, S., Holzer, S., Bradski, G., Konolige, K., and Navab, N. (2013). Computer Vision\u2013ACCV 2012, Proceedings of the 11th Asian Conference on Computer Vision, Daejeon, Republic of Korea, 5\u20139 November 2012, Springer. Revised Selected Papers; Part I 11."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Drost, B., Ulrich, M., Navab, N., and Ilic, S. (2010, January 13\u201318). Model globally, match locally: Efficient and robust 3D object recognition. Proceedings of the 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA.","DOI":"10.1109\/CVPR.2010.5540108"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Hinterstoisser, S., Lepetit, V., Wohlhart, P., and Konolige, K. (2018, January 8\u201314). On pre-trained image features and synthetic images for deep learning. Proceedings of the European Conference on Computer Vision (ECCV) Workshops, Munich, Germany.","DOI":"10.1007\/978-3-030-11009-3_42"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.cviu.2017.09.004","article-title":"A performance evaluation of point pair features","volume":"166","author":"Kiforenko","year":"2017","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Brachmann, E., Michel, F., Krull, A., Yang, M.Y., and Gumhold, S. (2016, January 27\u201330). Uncertainty-driven 6D pose estimation of objects and scenes from a single RGB image. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.366"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Kehl, W., Manhardt, F., Tombari, F., Ilic, S., and Navab, N. (2017, January 22\u201329). SSD-6D: Making RGB-based 3D detection and 6D pose estimation great again. Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy.","DOI":"10.1109\/ICCV.2017.169"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Doliotis, P., McMurrough, C.D., Criswell, A., Middleton, M.B., and Rajan, S.T. (2016, January 21\u201325). A 3D perception-based robotic manipulation system for automated truck unloading. Proceedings of the 2016 IEEE International Conference on Automation Science and Engineering (CASE), Fort Worth, TX, USA.","DOI":"10.1109\/COASE.2016.7743416"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Ali, W., Abdelkarim, S., Zidan, M., Zahran, M., and El Sallab, A. (2018, January 8\u201314). YOLO3D: End-to-end real-time 3D oriented object bounding box detection from lidar point cloud. Proceedings of the European Conference on Computer Vision (ECCV) Workshops, Munich, Germany.","DOI":"10.1007\/978-3-030-11015-4_54"},{"key":"ref_17","unstructured":"Jung, C.R., and Schramm, R. (2004, January 20). Rectangle detection based on a windowed Hough transform. Proceedings of the 17th Brazilian Symposium on Computer Graphics and Image Processing, Curitiba, Brazil."},{"key":"ref_18","first-page":"8","article-title":"Leaf identification using Harris corner detection, SURF feature and FLANN matcher","volume":"8","author":"George","year":"2021","journal-title":"Int. J. Innov. Technol. Explor. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1080\/01431161.2019.1641245","article-title":"An improved minimum bounding rectangle algorithm for regularized building boundary extraction from aerial LiDAR point clouds with partial occlusions","volume":"41","author":"Feng","year":"2019","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"7627","DOI":"10.1109\/LRA.2021.3100153","article-title":"FAITH: Fast iterative half-plane focus of expansion estimation using optic flow","volume":"6","author":"Dinaux","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"e2411","DOI":"10.1002\/nla.2411","article-title":"Least squares regression principal component analysis: A supervised dimensionality reduction method","volume":"29","author":"Pascual","year":"2022","journal-title":"Numer. Linear Algebra Appl."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., and Ng, A.Y. (2009, January 12\u201317). ROS: An open-source robot operating system. Proceedings of the ICRA Workshop on Open Source Software, Kobe, Japan.","DOI":"10.1109\/MRA.2010.936956"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/21\/8754\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:12:42Z","timestamp":1760130762000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/21\/8754"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,27]]},"references-count":22,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2023,11]]}},"alternative-id":["s23218754"],"URL":"https:\/\/doi.org\/10.3390\/s23218754","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,27]]}}}