Abstract
Logging harvesters represent a set of high-performance modern forestry machinery, which can finish a series of continuous operations such as felling, delimbing, peeling, bucking and so forth with human intervention. It is found by experiment that during the process of the alignment of the harvesting head to capture the trunk, the operator needs a lot of observation, judgment and repeated operations, which lead to the time and fuel losses. In order to improve the operation efficiency and reduce the operating costs, the point clouds for standing trees are collected with a low-cost 2D laser scanner. A cluster extracting algorithm and filtering algorithm are used to classify each trunk from the point cloud. On the assumption that every cross section of the target trunk is approximate a standard circle and combining the information of an Attitude and Heading Reference System, the radii and center locations of the trunks in the scanning range are calculated by the Fletcher-Reeves conjugate gradient algorithm. The method is validated through experiments in an aspen forest, and the optimized calculation time consumption is compared with the previous work of other researchers. Moreover, the implementation of the calculation result for automotive capturing trunks by the harvesting head during the logging operation is discussed in particular.
Highlights
Because the circumstances of forest areas are very complex and hazardous, it is very dangerous and laborious to harvest standing trees by hand-operated machines and tools
The Forest and Environment Equipment Research Institute of Beijing Forestry University has been dedicated to the research on logging harvesters for years [4,5]. It was found by experiments on logging harvester prototypes that the processes of delimbing, peeling, and bucking can be completed fast, but for the process of the alignment of harvesting head to capture the trunk, dues to the blind areas of the operator and vibration of the cane and vehicles chassis, the operator has to perform repeated observations, judgments and operations, which lead to the time and fuel losses
It is found by the experiments that the process of delimbing, peeling, and bucking can be completed fast by the logging harvester, but for the process of the alignment of the harvesting head to capture the trunk, the operator needs a lot of observation, judgment and repeated operations, which lead to time and fuel losses
Summary
Because the circumstances of forest areas are very complex and hazardous, it is very dangerous and laborious to harvest standing trees by hand-operated machines and tools. Miettinen et al [9,10] used 2D scanning laser range finders, machine vision systems and GPS to get information about the surrounding forest, such as tree diameters, positions and stem density. This information can be used on-line for the simultaneous localization and mapping for the forest harvesters or off-line in a forest asset management system.
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