{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T02:32:31Z","timestamp":1769913151848,"version":"3.49.0"},"reference-count":40,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2009,7,24]],"date-time":"2009-07-24T00:00:00Z","timestamp":1248393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This work proposes a new feature detection and description approach for mobile robot navigation using 2D laser range sensors. The whole process consists of two main modules: a sensor data segmentation module and a feature detection and characterization module. The segmentation module is divided in two consecutive stages: First, the segmentation stage divides the laser scan into clusters of consecutive range readings using a distance-based criterion. Then, the second stage estimates the curvature function associated to each cluster and uses it to split it into a set of straight-line and curve segments. The curvature is calculated using a triangle-area representation where, contrary to previous approaches, the triangle side lengths at each range reading are adapted to the local variations of the laser scan, removing noise without missing relevant points. This representation remains unchanged in translation or rotation, and it is also robust against noise. Thus, it is able to provide the same segmentation results although the scene will be perceived from different viewpoints. Therefore, segmentation results are used to characterize the environment using line and curve segments, real and virtual corners and edges. Real scan data collected from different environments by using different platforms are used in the experiments in order to evaluate the proposed environment description algorithm.<\/jats:p>","DOI":"10.3390\/s90805894","type":"journal-article","created":{"date-parts":[[2009,7,24]],"date-time":"2009-07-24T12:09:56Z","timestamp":1248437396000},"page":"5894-5918","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":41,"title":["Curvature-Based Environment Description for Robot Navigation Using Laser Range Sensors"],"prefix":"10.3390","volume":"9","author":[{"given":"Ricardo","family":"V\u00e1zquez-Mart\u00edn","sequence":"first","affiliation":[{"name":"Departamento de Tecnolog\u00eda Electr\u00f3nica, University of M\u00e1laga, E.T.S.I. Telecomunicaci\u00f3n, Campus Teatinos, M\u00e1laga, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pedro","family":"N\u00fa\u00f1ez","sequence":"additional","affiliation":[{"name":"Departamento de los Computadores y las Comunicaciones, University of Extremadura, Escuela Polit\u00e9cnica, C\u00e1ceres, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antonio","family":"Bandera","sequence":"additional","affiliation":[{"name":"Departamento de Tecnolog\u00eda Electr\u00f3nica, University of M\u00e1laga, E.T.S.I. Telecomunicaci\u00f3n, Campus Teatinos, M\u00e1laga, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9235-7856","authenticated-orcid":false,"given":"Francisco","family":"Sandoval","sequence":"additional","affiliation":[{"name":"Departamento de Tecnolog\u00eda Electr\u00f3nica, University of M\u00e1laga, E.T.S.I. Telecomunicaci\u00f3n, Campus Teatinos, M\u00e1laga, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2009,7,24]]},"reference":[{"key":"ref_1","unstructured":"Roumeliotis, S., and Bekey, G.B. (\u2013, January November). Segments: A Layered, Dual-Kalman Filter Algorithm for Indoor Feature Extraction. Kagawa University, Takamatsu, Japan."},{"key":"ref_2","first-page":"311","article-title":"Robust mapping and localization in indoor environments using sonar data","volume":"40","author":"Neira","year":"2002","journal-title":"Int. J. Robot. Res"},{"key":"ref_3","unstructured":"Crowley, J. (1989, January May). World Modeling and Position Estimation for a Mobile Robot Using Ultrasonic Ranging. Scottsdale, USA."},{"key":"ref_4","unstructured":"Gutmann, J., and Schlegel, C. (1996, January October). AMOS: Comparison of Scan Matching Approaches for Self-Localization in Indoor Environments. 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