Tensometry of soft biological tissues with manipulation robot

Arkhipov, M. V.; Vzhesnevsky, E. A.; Eremushkin, M. A.; Samorukov, E A; Kocherevskaya, L B

doi:10.1088/1757-899x/489/1/012051

Cited by 5 publications

(1 citation statement)

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“…One of the relevant modern approaches for solving this problem, which do not require highly qualified (and therefore highly paid) personnel for retranslation of knowledge and experience on the part of the customer of such work and the contractor is the use of modern mathematical methods of machine learning to help operators of multi-operator forest machines. This approach is proposed to be used not only for logging round timber, but also at every stage of the logging process [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Stem segmentation for sustainable forest management task

et al. 2023

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Harvesting of forest raw materials, namely felling and bucking of log on forest areas, is the first and main stage in the logging chain. One of the problems in this industry is the shortage of highly qualified specialists-operators of forest machines, including feller-delimbing-bucking machines (harvesters). Operators who have just come to the industry or have insufficient experience (have worked for less than a year) cannot correctly configure harvesters, as a result of which the processes in the logging chain are disrupted. Thus, it becomes necessary to apply additional models of working with operators and forest machines to reduce the resulting costs for the company. Understanding how much wood raw material will be obtained from the logging site allows predicting not only the amount of equipment required, but also planning actions for the next stages of logging.

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Section: Introductionmentioning

confidence: 99%