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Inspection planning can be computationally challenging, as the search space over motion plans grows exponentially with the number of points of interest to inspect. We propose a novel method, Incremental Random Inspection-roadmap Search (IRIS), that computes inspection plans whose length and set of successfully inspected points asymptotically converge to those of an optimal inspection plan. IRIS incrementally densifies a motion-planning roadmap using a sampling-based algorithm and performs efficient near-optimal graph search over the resulting roadmap as it is generated. We prove the resulting algorithm is asymptotically optimal under very general assumptions about the robot and the environment. We demonstrate IRIS\u2019s efficacy on a simulated inspection task with a planar five DOF manipulator, on a simulated bridge inspection task with an Unmanned Aerial Vehicle (UAV), and on a medical endoscopic inspection task for a continuum parallel surgical robot in cluttered human anatomy. In all these systems IRIS computes higher-quality inspection plans orders of magnitudes faster than a prior state-of-the-art method.<\/jats:p>","DOI":"10.1177\/02783649231171646","type":"journal-article","created":{"date-parts":[[2023,6,21]],"date-time":"2023-06-21T04:46:08Z","timestamp":1687322768000},"page":"150-175","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Asymptotically optimal inspection planning via efficient near-optimal search on sampled roadmaps"],"prefix":"10.1177","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5237-1220","authenticated-orcid":false,"given":"Mengyu","family":"Fu","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alan","family":"Kuntz","sequence":"additional","affiliation":[{"name":"Robotics Center and Kahlert School of Computing, University of Utah, Salt Lake City, UT, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oren","family":"Salzman","sequence":"additional","affiliation":[{"name":"Computer Science Department, Technion - Israel Institute of Technology, Haifa, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4492-1384","authenticated-orcid":false,"given":"Ron","family":"Alterovitz","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2023,6,21]]},"reference":[{"key":"bibr1-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1609\/socs.v5i1.18306"},{"key":"bibr2-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1177\/1729881416663664"},{"key":"bibr3-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2017.2678606"},{"key":"bibr4-02783649231171646","volume-title":"ASCE 2017 Infrastructure Report Card","author":"ASCE","year":"2016"},{"key":"bibr5-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1002\/rob.20350"},{"key":"bibr6-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2015.7140101"},{"key":"bibr7-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1017\/S0263574716000084"},{"key":"bibr8-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1007\/s10514-015-9517-1"},{"key":"bibr9-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2018.2827161"},{"key":"bibr10-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2000.844107"},{"key":"bibr11-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1016\/j.sbspro.2013.05.030"},{"key":"bibr12-02783649231171646","volume-title":"Principles of Robot Motion: Theory, Algorithms, and Implementation","author":"Choset HM","year":"2005"},{"key":"bibr13-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2000.844726"},{"key":"bibr14-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1609\/icaps.v26i1.13788"},{"key":"bibr15-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1007\/BF01386390"},{"key":"bibr16-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2016.2635107"},{"key":"bibr17-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1007\/s002910000046"},{"key":"bibr18-02783649231171646","volume-title":"TurboSquid","author":"Elkassar","year":"2008"},{"key":"bibr19-02783649231171646","doi-asserted-by":"publisher","DOI":"10.1609\/icaps.v22i1.13529"},{"key":"bibr20-02783649231171646","first-page":"327","volume-title":"Int. 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