Forestry crane posture estimation with a two dimensional laser scanner

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Title: Forestry crane posture estimation with a two dimensional laser scanner
Author: Hyyti, Heikki; Lehtola, Ville; Visala, Arto
Publisher: Wiley Periodicals, Inc.
Date: 2018
Language: en
Belongs to series: Journal of Field Robotics
ISSN: 1556-4959
Abstract: Crane posture estimation is the stepping stone to forest machine automation. Here, we introduce a robust minimal perception solution, that is, one that uses minimal con-straints for maximal benefits. Specifically, we introduce a robust particle‐filter‐based method to estimate and track the posture of a flexible hydraulic crane by using only low‐cost equipment, namely, a two‐dimensional (2D) laser scanner, two short magnetically attached metal tubes as targets, and an angle sensor. An important feature of our method is that it incorporates control signals for hydraulic actuators. In contrast to the previous works employing laser scanners, we do not use the full shape of the crane to estimate the crane posture, but, instead, we use only two small targets in the field of view of the laser scanner. Thus, a large share of the range data is useful for other purposes, for example, to map the surrounding environment. We test the proposed method in a challenging forest environment and show that the particle filter is able to estimate the posture of the hy-draulic crane efficiently and reliably in the presence of oc-clusions and obstructions. During our comprehensive test-ing, the tip position was measured with average errors smaller than 4.3 cm whereas the absolute maximum error was 15 cm.
Subject: forestry
laser scanning
position estimation

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