{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:56:57Z","timestamp":1754157417181,"version":"3.41.2"},"reference-count":22,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2012,4,27]],"date-time":"2012-04-27T00:00:00Z","timestamp":1335484800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,4,27]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to describe a novel application of the well\u2010established 2D laser scan\u2010matching technique for self\u2010localization of a walking robot. The techniques described in this paper enable a walking robot with a 2D laser scanner to obtain precise maps of man\u2010made environments, which can be useful in search and reconnaissance missions, e.g. in warehouses, production plants, and other industrial areas.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>The presented system combines two scan\u2010matching algorithms (PSM and PLICP) to deal with low\u2010quality range data from a compact laser scanner and to provide robust self\u2010localization in various types of man\u2010made environments. Data from proprioceptive sensors and simplifying assumptions holding in man\u2010made environments are exploited to compensate for the varying attitude of the walking robot, particularly in uneven terrain.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>The experimental results suggest that neglecting either the poor initial pose guess obtained from the legged odometry, or the varying attitude angles of a walking robot's body, may lead to unacceptable results in self\u2010localization and scan\u2010based mapping. It is also demonstrated that using the PSM algorithm to compute the initial pose estimate for the more precise PLICP scan\u2010matching algorithm improves the results of self\u2010localization.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Research limitations\/implications<\/jats:title><jats:p>So far, the presented self\u2010localization system was tested in limited\u2010scale indoor experiments. Experiments with more extended and realistic scenarios are scheduled as further work.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title><jats:p>Applying techniques described in this paper, the author was able to obtain the robot pose and precise maps of man\u2010made environments, which can be useful in USAR and reconnaissance missions, also in warehouses, production plants, and other industrial areas.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>The scan\u2010matching algorithms used in the presented research are not new, the contribution lies in combining them in order to overcome issues specific to a small\u2010size legged platform, using only common affordable hardware.<\/jats:p><\/jats:sec>","DOI":"10.1108\/01439911211217062","type":"journal-article","created":{"date-parts":[[2012,4,28]],"date-time":"2012-04-28T07:19:52Z","timestamp":1335597592000},"page":"242-250","source":"Crossref","is-referenced-by-count":11,"title":["Laser scan matching for self\u2010localization of a walking robot in man\u2010made environments"],"prefix":"10.1108","volume":"39","author":[{"given":"Piotr","family":"Skrzypczynski","sequence":"first","affiliation":[]}],"member":"140","reference":[{"doi-asserted-by":"crossref","unstructured":"Belter, D. and Skrzypczy\u0144ski, P. 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