{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T10:55:27Z","timestamp":1779101727902,"version":"3.51.4"},"reference-count":50,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,6,9]],"date-time":"2020-06-09T00:00:00Z","timestamp":1591660800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Academy of Finland grant","award":["328755"],"award-info":[{"award-number":["328755"]}]},{"name":"Business Finland grant","award":["26004155"],"award-info":[{"award-number":["26004155"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Autonomous harvesting and transportation is a long-term goal of the forest industry. One of the main challenges is the accurate localization of both vehicles and trees in a forest. Forests are unstructured environments where it is difficult to find a group of significant landmarks for current fast feature-based place recognition algorithms. This paper proposes a novel approach where local point clouds are matched to a global tree map using the Delaunay triangularization as the representation format. Instead of point cloud based matching methods, we utilize a topology-based method. First, tree trunk positions are registered at a prior run done by a forest harvester. Second, the resulting map is Delaunay triangularized. Third, a local submap of the autonomous robot is registered, triangularized and matched using triangular similarity maximization to estimate the position of the robot. We test our method on a dataset accumulated from a forestry site at Lieksa, Finland. A total length of 200 m of harvester path was recorded by an industrial harvester with a 3D laser scanner and a geolocation unit fixed to the frame. Our experiments show a 12 cm s.t.d. in the location accuracy and with real-time data processing for speeds not exceeding 0.5 m\/s. The accuracy and speed limit are realistic during forest operations.<\/jats:p>","DOI":"10.3390\/rs12111870","type":"journal-article","created":{"date-parts":[[2020,6,9]],"date-time":"2020-06-09T06:34:16Z","timestamp":1591684456000},"page":"1870","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":53,"title":["Localization in Unstructured Environments: Towards Autonomous Robots in Forests with Delaunay Triangulation"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6556-2213","authenticated-orcid":false,"given":"Qingqing","family":"Li","sequence":"first","affiliation":[{"name":"Turku Intelligent Embedded and Robotic Systems, University of Turku, 20500 Turku, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7646-929X","authenticated-orcid":false,"given":"Paavo","family":"Nevalainen","sequence":"additional","affiliation":[{"name":"Turku Intelligent Embedded and Robotic Systems, University of Turku, 20500 Turku, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3091-3217","authenticated-orcid":false,"given":"Jorge","family":"Pe\u00f1a Queralta","sequence":"additional","affiliation":[{"name":"Turku Intelligent Embedded and Robotic Systems, University of Turku, 20500 Turku, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2468-5708","authenticated-orcid":false,"given":"Jukka","family":"Heikkonen","sequence":"additional","affiliation":[{"name":"Turku Intelligent Embedded and Robotic Systems, University of Turku, 20500 Turku, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1793-2694","authenticated-orcid":false,"given":"Tomi","family":"Westerlund","sequence":"additional","affiliation":[{"name":"Turku Intelligent Embedded and Robotic Systems, University of Turku, 20500 Turku, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.isprsjprs.2014.08.008","article-title":"Accuracy in estimation of timber assortments and stem distribution\u2014A comparison of airborne and terrestrial laser scanning techniques","volume":"97","author":"Kankare","year":"2014","journal-title":"ISPRS J. 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