{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:25:30Z","timestamp":1750220730779,"version":"3.41.0"},"reference-count":30,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2021,7,22]],"date-time":"2021-07-22T00:00:00Z","timestamp":1626912000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2017YFA0700800"],"award-info":[{"award-number":["2017YFA0700800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Key Research and Development Program of Shaanxi","award":["2021GY-025"],"award-info":[{"award-number":["2021GY-025"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61573273 and 61790563"],"award-info":[{"award-number":["61573273 and 61790563"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Fundamental Research Funds for Central Universities","award":["xzy012019045 and xjj2018214"],"award-info":[{"award-number":["xzy012019045 and xjj2018214"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Internet Technol."],"published-print":{"date-parts":[[2021,11,30]]},"abstract":"<jats:p>Building an accurate map is essential for autonomous robot navigation in the environment without GPS. Compared with single-robot, the multiple-robot system has much better performance in terms of accuracy, efficiency and robustness for the simultaneous localization and mapping (SLAM). As a critical component of multiple-robot SLAM, the problem of map merging still remains a challenge. To this end, this article casts it into point set registration problem and proposes an effective map merging method based on the context-based descriptors and correspondence expansion. It first extracts interest points from grid maps by the Harris corner detector. By exploiting neighborhood information of interest points, it automatically calculates the maximum response radius as scale information to compute the context-based descriptor, which includes eigenvalues and normals computed from local structures of each interest point. Then, it effectively establishes origin matches with low precision by applying the nearest neighbor search on the context-based descriptor. Further, it designs a scale-based corresponding expansion strategy to expand each origin match into a set of feature matches, where one similarity transformation between two grid maps can be estimated by the Random Sample Consensus algorithm. Subsequently, a measure function formulated from the trimmed mean square error is utilized to confirm the best similarity transformation and accomplish the coarse map merging. Finally, it utilizes the scaling trimmed iterative closest point algorithm to refine initial similarity transformation so as to achieve accurate merging. As the proposed method considers scale information in the context-based descriptor, it is able to merge grid maps in diverse resolutions. Experimental results on real robot datasets demonstrate its superior performance over other related methods on accuracy and robustness.<\/jats:p>","DOI":"10.1145\/3403948","type":"journal-article","created":{"date-parts":[[2021,7,22]],"date-time":"2021-07-22T14:32:41Z","timestamp":1626964361000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Merging Grid Maps in Diverse Resolutions by the Context-based Descriptor"],"prefix":"10.1145","volume":"21","author":[{"given":"Zhiyang","family":"Lin","sequence":"first","affiliation":[{"name":"Xi\u2019an Jiaotong Universiy, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jihua","family":"Zhu","sequence":"additional","affiliation":[{"name":"Xi\u2019an Jiaotong Universiy, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zutao","family":"Jiang","sequence":"additional","affiliation":[{"name":"Xi\u2019an Jiaotong Universiy, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yujie","family":"Li","sequence":"additional","affiliation":[{"name":"Yangzhou University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaochen","family":"Li","sequence":"additional","affiliation":[{"name":"Xi\u2019an Jiaotong Universiy, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongyu","family":"Li","sequence":"additional","affiliation":[{"name":"Xi\u2019an Jiaotong Universiy, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,7,22]]},"reference":[{"volume-title":"Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA\u201915)","author":"Akdeniz Bayram C.","key":"e_1_2_1_1_1"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2006.876965"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0263574712000732"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2016.2624754"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10514-008-9097-4"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2005.07.001"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2004.05.007"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3306346.3322942"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.5555\/2976248.2976291"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/BRACIS.2017.69"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2019.2899783"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10846-018-0895-4"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2016.2517210"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2700727"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2014.2309639"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2012.10.004"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2020.2984991"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0263574715000168"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2017.2705103"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3303848"},{"volume-title":"Proceedings of the 2016 IEEE International Conference on Robotics and Automation (ICRA\u201916)","author":"Rosen David M.","key":"e_1_2_1_21_1"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1049\/el.2010.3403"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2014.06.002"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1002\/rob.21812"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3362123"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569433"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2928180"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2967597"},{"key":"e_1_2_1_29_1","first-page":"180","article-title":"Merging grid maps via point set registration","volume":"28","author":"Zhu Jihua","year":"2013","journal-title":"Int. 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