Skip to the main content

Original scientific paper

https://doi.org/10.5552/crojfe.2023.2056

Realization of Autonomous Detection, Positioning and Angle Estimation of Harvested Logs

Songyu Li ; Luleå University of Technology Department of Engineering Sciences and Mathematics 97187 Luleå SWEDEN *
Håkan Lideskog ; Luleå University of Technology Department of Engineering Sciences and Mathematics 97187 Luleå SWEDEN

* Corresponding author.


Full text: english pdf 3.603 Kb

page 369-383

downloads: 135

cite


Abstract

To further develop forest production, higher automation of forest operations is required. Such endeavour promotes research on unmanned forest machines. Designing unmanned forest machines that exercise forwarding requires an understanding of positioning and angle estimations of logs after cutting and delimbing have been conducted, as support for subsequent crane loading work. This study aims to improve the automation of the forwarding operation and presents a system to realize real-time automatic detection, positioning, and angle estimation of harvested logs implemented on an existing unmanned forest machine experimental platform from the AORO (Arctic Off-Road Robotics) Lab. This system uses ROS as the underlying software architecture and a Zed2 camera and NVIDIA JETSON AGX XAVIER as the imaging sensor and computing platform, respectively, utilizing the YOLOv3 algorithm for real-time object detection. Moreover, the study combines the processing of depth data and depth to spatial transform to realize the calculation of the relative location of the target log related to the camera. On this basis, the angle estimation of the target log is further realized by image processing and color analysis. Finally, the absolute position and log angles are determined by the spatial coordinate transformation of the relative position data. This system was tested and validated using a pre-trained log detector for birch with a mean average precision (mAP) of 80.51%. Log positioning mean error did not exceed 0.27 m and the angle estimation mean error was less than 3 degrees during the tests. This log pose estimation method could encompass one important part of automated forwarding operations.

Keywords

log detection; autonomous forwarding; log grasping

Hrčak ID:

310153

URI

https://hrcak.srce.hr/310153

Publication date:

14.7.2023.

Visits: 383 *