{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,24]],"date-time":"2025-05-24T07:26:46Z","timestamp":1748071606526},"reference-count":14,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2007,3,13]],"date-time":"2007-03-13T00:00:00Z","timestamp":1173744000000},"content-version":"vor","delay-in-days":5306,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Robotic Syst."],"published-print":{"date-parts":[[1992,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Many types of existing vehicles contain an inertial navigation system (INS) that can be utilized to greatly improve the performance of motion analysis techniques and make them useful for practical military and civilian applications. This article presents the results obtained with a maximally passive system of obstacle detection for ground\u2010based vehicles and rotorcraft. Automatic detection of these obstacles and the necessary guidance and control actions triggered by such detection will facilitate autonomous vehicle navigation. Our approach to obstacle detection employs motion analysis of imagery collected by a passive sensor during vehicle travel to generate range measurements to world points within the field of view of the sensor. The approach makes use of INS data and scene analysis results to improve interest point selection, the matching of the interest points, and the subsequent motion\u2010based range computations, tracking, and obstacle detection. In this article, we concentrate on the results obtained using lab and outdoor imagery. The range measurements that are made by INS integrated motion analysis are compared to a limited amount of ground truth that is available. \u00a9 1992 John Wiley &amp; Sons, Inc.<\/jats:p>","DOI":"10.1002\/rob.4620090608","type":"journal-article","created":{"date-parts":[[2007,7,6]],"date-time":"2007-07-06T13:14:33Z","timestamp":1183727673000},"page":"817-842","source":"Crossref","is-referenced-by-count":12,"title":["Inertial navigation sensor integrated motion analysis for autonomous vehicle navigation"],"prefix":"10.1002","volume":"9","author":[{"given":"Barry","family":"Roberts","sequence":"first","affiliation":[]},{"given":"Bir","family":"Bhanu","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2007,3,13]]},"reference":[{"key":"e_1_2_1_2_2","unstructured":"M. J.Daily J. G.Harris andK.Reiser \u201cDetecting obstacles in range imagery \u201d in Proc. of DARPA Image Understanding Workshop February1987 pp.87\u201397."},{"key":"e_1_2_1_3_2","volume-title":"Millimeter\u2010wave radar may enhance safety of helicopter flights","year":"1987"},{"key":"e_1_2_1_4_2","unstructured":"C.Thorpe S.Schafer andT.Kanade \u201cVision and navigation for the Carnegie Mellon Navlab \u201d in Proc. of DARPA Image Understanding Workshop February1987 pp.143\u2013153."},{"key":"e_1_2_1_5_2","unstructured":"B.BhanuandB.Roberts \u201cObstacle detection during rotorcraft low\u2010altitude flight \u201d annual technical report to NASA\u2010Ames April1989."},{"key":"e_1_2_1_6_2","unstructured":"B.Bhanu B.Roberts andJ. C.Ming \u201cInertial navigation sensor integrated motion analysis \u201d Proc. of DARPA Image Understanding Workshop May1989 pp.747\u2013763."},{"key":"e_1_2_1_7_2","unstructured":"R.Dutta R.Manmatha E. M.Riseman andM. 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