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Open AccessArticle

Localization in Unstructured Environments: Towards Autonomous Robots in Forests with Delaunay Triangulation

Turku Intelligent Embedded and Robotic Systems, University of Turku, 20500 Turku, Finland
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(11), 1870;
Received: 7 May 2020 / Revised: 31 May 2020 / Accepted: 5 June 2020 / Published: 9 June 2020
(This article belongs to the Section Forest Remote Sensing)
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. View Full-Text
Keywords: robotics; localization; delaunay triangulation; SLAM; forest localization robotics; localization; delaunay triangulation; SLAM; forest localization
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MDPI and ACS Style

Li, Q.; Nevalainen, P.; Peña Queralta, J.; Heikkonen, J.; Westerlund, T. Localization in Unstructured Environments: Towards Autonomous Robots in Forests with Delaunay Triangulation. Remote Sens. 2020, 12, 1870.

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