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Automated Driving on a Skid Road with a Forwarder in a CTL Logging Process

Geiger, Chris; Beiser, Sebastian; Geimer, Marcus

Abstract (englisch):

In a fully mechanized Cut-to-Length (CTL) logging process, a harvester fells the trees and cuts them into logs of specific length according to the log quality. In the subsequent process step, a forwarder loads the logs and moves them from the logging area to a forest road. This step shows a huge potential towards automation. Within this paper, a method is presented for driving a forwarder automated on a skid road based on environmental recognition, avoiding the disadvantages of gps-based systems and their lacking accuracy under tree canopy. The presented method exploits the process flow of a CTL process, as a Lidar is mounted on the harvester, which delivers a highly accurate point cloud of the environment and works well regardless of the lighting conditions. Applying the SLAM-algorithm ‘Google Cartographer’ on the collected point cloud data of the 3D-LIDAR from the Harvester creates a map, on which an offline path planning is performed. This map results firstly in a 2D occupancy grid map, showing which areas contains objects and which areas are free space. The data in the map is further processed by identifying trees using a clustering algorithm on the object points. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000139443
Veröffentlicht am 17.11.2021
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Fahrzeugsystemtechnik (FAST)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2021
Sprache Englisch
Identifikator KITopen-ID: 1000139443
Erschienen in Proceedings of The Joint 43rd Annual Meeting of Council on Forest Engineering (COFE) & the 53rd International Symposium on Forest Mechanization (FORMEC), Forest Engineering Family – Growing Forward Together, September 27-30, 2021, Corvallis, Oregon, U.S.A. Ed.: W. Chung
Veranstaltung COFE-FORMEC. Joint Meeting (2021), Online, 27.09.2021 – 30.09.2021
Seiten 135
Vorab online veröffentlicht am 26.10.2021
Externe Relationen Abstract/Volltext
Schlagwörter Pathplanning, Potential Fields, Automation, Automated Driving
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