{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T16:36:55Z","timestamp":1775147815490,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,6,12]],"date-time":"2021-06-12T00:00:00Z","timestamp":1623456000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key R&amp;D Program of China","award":["Grant 2019YFB1703600"],"award-info":[{"award-number":["Grant 2019YFB1703600"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Grants 62033001, 51709023"],"award-info":[{"award-number":["Grants 62033001, 51709023"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this work, we propose a novel coarse-to-fine method for object pose estimation coupled with admittance control to promote robotic shaft-in-hole assembly. Considering that traditional approaches to locate the hole by force sensing are time-consuming, we employ 3D vision to estimate the axis pose of the hole. Thus, robots can locate the target hole in both position and orientation and enable the shaft to move into the hole along the axis orientation. In our method, first, the raw point cloud of a hole is processed to acquire the keypoints. Then, a coarse axis is extracted according to the geometric constraints between the surface normals and axis. Lastly, axis refinement is performed on the coarse axis to achieve higher precision. Practical experiments verified the effectiveness of the axis pose estimation. The assembly strategy composed of axis pose estimation and admittance control was effectively applied to the robotic shaft-in-hole assembly.<\/jats:p>","DOI":"10.3390\/s21124064","type":"journal-article","created":{"date-parts":[[2021,6,14]],"date-time":"2021-06-14T22:25:46Z","timestamp":1623709546000},"page":"4064","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["A Coarse-to-Fine Method for Estimating the Axis Pose Based on 3D Point Clouds in Robotic Cylindrical Shaft-in-Hole Assembly"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2481-6018","authenticated-orcid":false,"given":"Can","family":"Li","sequence":"first","affiliation":[{"name":"College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China"},{"name":"State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1011-2906","authenticated-orcid":false,"given":"Ping","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China"},{"name":"State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China"}]},{"given":"Xin","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China"},{"name":"State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5510-5083","authenticated-orcid":false,"given":"Xinyu","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China"},{"name":"State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China"}]},{"given":"Aijun","family":"Yin","sequence":"additional","affiliation":[{"name":"College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China"},{"name":"State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Stolt, A., Linderoth, M., Robertsson, A., and Johansson, R. (2012, January 14\u201318). Force controlled robotic assembly without a force sensor. Proceedings of the 2012 IEEE International Conference on Robotics and Automation, Saint Paul, MN, USA.","DOI":"10.1109\/ICRA.2012.6224837"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/j.rcim.2012.09.001","article-title":"Robotic assembly automation using robust compliant control","volume":"29","author":"Chen","year":"2013","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Fang, S., Huang, X., Chen, H., and Xi, N. (2016, January 3\u20137). Dual-arm robot assembly system for 3C product based on vision guidance. Proceedings of the 2016 IEEE International Conference on Robotics and Biomimetics (ROBIO), Qingdao, China.","DOI":"10.1109\/ROBIO.2016.7866422"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"107991","DOI":"10.1016\/j.measurement.2020.107991","article-title":"A calibration strategy for visually guided robot assembly system of large cabin","volume":"163","author":"Jiang","year":"2020","journal-title":"Measurement"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"108294","DOI":"10.1016\/j.measurement.2020.108294","article-title":"Development of a novel integrated automated assembly system for large volume components in outdoor environment","volume":"168","author":"Peng","year":"2020","journal-title":"Measurement"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.procir.2014.10.077","article-title":"Position identification in force-guided robotic peg-in-hole assembly tasks","volume":"23","author":"Jasim","year":"2014","journal-title":"Procedia Cirp"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1080\/01691864.2015.1130172","article-title":"Guidance algorithm for complex-shape peg-in-hole strategy based on geometrical information and force control","volume":"30","author":"Song","year":"2016","journal-title":"Adv. Robot."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Gao, F., Zhao, Y., and Chen, Z. (2020). Peg-in-Hole Assembly Based on Six-Legged Robots with Visual Detecting and Force Sensing. Sensors, 20.","DOI":"10.3390\/s20102861"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3008","DOI":"10.1109\/JSEN.2018.2889469","article-title":"Pose measurement and motion estimation of space non-cooperative targets based on laser radar and stereo-vision fusion","volume":"19","author":"Peng","year":"2018","journal-title":"IEEE Sens. J."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"107452","DOI":"10.1016\/j.measurement.2019.107452","article-title":"A novel method for measuring pose of hydraulic supports relative to inspection robot using LiDAR","volume":"154","author":"Yang","year":"2020","journal-title":"Measurement"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"108760","DOI":"10.1016\/j.measurement.2020.108760","article-title":"Pose Calibration of Line Structured Light Probe Based on Ball Bar Target in Cylindrical Coordinate Measuring Machines","volume":"171","author":"Wang","year":"2020","journal-title":"Measurement"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"68030","DOI":"10.1109\/ACCESS.2020.2986470","article-title":"Evaluation of the ICP Algorithm in 3D Point Cloud Registration","volume":"8","author":"Li","year":"2020","journal-title":"IEEE Access"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2241","DOI":"10.1109\/TPAMI.2015.2513405","article-title":"Go-ICP: A globally optimal solution to 3D ICP point-set registration","volume":"38","author":"Yang","year":"2015","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Zhou, Q.Y., Park, J., and Koltun, V. (2016, January 11\u201314). Fast global registration. Proceedings of the European Conference on Computer Vision, Amsterdam, The Netherlands.","DOI":"10.1007\/978-3-319-46475-6_47"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"73637","DOI":"10.1109\/ACCESS.2019.2919989","article-title":"Point cloud registration based on MCMC-SA ICP algorithm","volume":"7","author":"Liu","year":"2019","journal-title":"IEEE Access"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Papazov, C., and Burschka, D. (2010, January 8\u201312). An efficient ransac for 3D object recognition in noisy and occluded scenes. Proceedings of the Asian Conference on Computer Vision, Queenstown, New Zealand.","DOI":"10.1007\/978-3-642-19315-6_11"},{"key":"ref_17","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_18","doi-asserted-by":"crossref","unstructured":"Guo, Y., Wang, H., Hu, Q., Liu, H., Liu, L., and Bennamoun, M. (2020). Deep learning for 3d point clouds: A survey. IEEE Trans. Pattern Anal. Mach. Intell.","DOI":"10.1109\/TPAMI.2020.3005434"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wong, J.M., Kee, V., Le, T., Wagner, S., Mariottini, G.L., Schneider, A., Hamilton, L., Chipalkatty, R., Hebert, M., and Johnson, D.M. (2017, January 24\u201328). Segicp: Integrated deep semantic segmentation and pose estimation. Proceedings of the 2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada.","DOI":"10.1109\/IROS.2017.8206470"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Wang, C., Xu, D., Zhu, Y., Mart\u00edn-Mart\u00edn, R., Lu, C., Fei-Fei, L., and Savarese, S. (2019, January 15\u201320). Densefusion: 6d object pose estimation by iterative dense fusion. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA.","DOI":"10.1109\/CVPR.2019.00346"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1145\/358669.358692","article-title":"Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography","volume":"24","author":"Fischler","year":"1981","journal-title":"Commun. ACM"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/0031-3203(81)90009-1","article-title":"Generalizing the Hough transform to detect arbitrary shapes","volume":"13","author":"Ballard","year":"1981","journal-title":"Pattern Recognit."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1905","DOI":"10.1111\/j.1467-8659.2010.01658.x","article-title":"Hierarchical structure recovery of point-sampled surfaces","volume":"Volume 29","author":"Attene","year":"2010","journal-title":"Computer Graphics Forum"},{"key":"ref_24","unstructured":"Chaperon, T., and Goulette, F. (2001, January 21\u201323). Extracting Cylinders in Full 3D Data Using a Random Sampling Method and the Gaussian Image. Proceedings of the Vision Modeling and Visualization Conference 2001 (VMV-01), Stuttgart, Germany."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1111\/j.1467-8659.2007.01016.x","article-title":"Efficient RANSAC for Point-Cloud Shape Detection","volume":"26","author":"Schnabel","year":"2007","journal-title":"Comput. Graph. Forum"},{"key":"ref_26","first-page":"60","article-title":"Efficient hough transform for automatic detection of cylinders in point clouds","volume":"3","author":"Rabbani","year":"2005","journal-title":"Isprs Wg Iii\/3 Iii\/4"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1242","DOI":"10.1016\/j.optlaseng.2012.03.014","article-title":"Best ellipse and cylinder parameters estimation from laser profile scan sections","volume":"50","author":"Rahayem","year":"2012","journal-title":"Opt. Lasers Eng."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/j.cam.2012.09.037","article-title":"Fitting cylinders to data","volume":"239","author":"Nievergelt","year":"2013","journal-title":"J. Comput. Appl. Math."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1016\/j.cag.2014.09.027","article-title":"Extraction of cylinders and estimation of their parameters from point clouds","volume":"46","author":"Tran","year":"2015","journal-title":"Comput. Graph."},{"key":"ref_30","first-page":"13","article-title":"As-built modeling of piping system from terrestrial laser-scanned point clouds using normal-based region growing","volume":"1","author":"Kawashima","year":"2014","journal-title":"J. Comput. Des. Eng."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1016\/j.measurement.2019.01.095","article-title":"Robust cylinder fitting in laser scanning point cloud data","volume":"138","author":"Nurunnabi","year":"2019","journal-title":"Measurement"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1115\/1.3140702","article-title":"Impedance control: An approach to manipulation: Part I\u2014Theory","volume":"107","author":"Hogan","year":"1985","journal-title":"J. Dyn. Sys. Meas. Control."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Ott, C., Mukherjee, R., and Nakamura, Y. (2010, January 3\u20137). Unified impedance and admittance control. Proceedings of the 2010 IEEE International Conference on Robotics and Automation, Anchorage, AK, USA.","DOI":"10.1109\/ROBOT.2010.5509861"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1007\/s13218-010-0059-6","article-title":"Semantic 3D object maps for everyday manipulation in human living environments","volume":"24","author":"Rusu","year":"2010","journal-title":"KI-K\u00fcnstliche Intell."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Klasing, K., Althoff, D., Wollherr, D., and Buss, M. (2009, January 12\u201317). Comparison of surface normal estimation methods for range sensing applications. Proceedings of the 2009 IEEE international conference on robotics and automation, Kobe, Japan.","DOI":"10.1109\/ROBOT.2009.5152493"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Chebrolu, N., L\u00e4be, T., Vysotska, O., Behley, J., and Stachniss, C. (2020). Adaptive Robust Kernels for Non-Linear Least Squares Problems. arXiv.","DOI":"10.1109\/LRA.2021.3061331"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1002\/wics.101","article-title":"Principal component analysis","volume":"2","author":"Abdi","year":"2010","journal-title":"Wiley Interdiscip. Rev. Comput. Stat."},{"key":"ref_38","first-page":"586","article-title":"Method for registration of 3-D shapes","volume":"Volume 1611","author":"Besl","year":"1992","journal-title":"Sensor Fusion IV: Control Paradigms and Data Structures"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/12\/4064\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:13:47Z","timestamp":1760163227000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/12\/4064"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,12]]},"references-count":38,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2021,6]]}},"alternative-id":["s21124064"],"URL":"https:\/\/doi.org\/10.3390\/s21124064","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,12]]}}}