Estimating the position of the harvester head: a key step towards the precision forestry of the future?
2015 (English)In: Croatian Journal of Forest Engineering, ISSN 1845-5719, E-ISSN 1848-9672, Vol. 36, no 2, 147-164 p.Article in journal (Refereed) Published
Modern harvesters are technologically sophisticated, with many useful features such as the ability to automatically measure stem diameters and lengths. This information is processed in real time to support value optimization when cutting stems into logs. It can also be transferred from the harvesters to centralized systems and used for wood supply management. Such information management systems have been available since the 1990s in Sweden and Finland, and are constantly being upgraded. However, data on the position of the harvester head relative to the machine are generally not recorded during harvesting. The routine acquisition and analysis of such data could offer several opportunities to improve forestry operations and related processes in the future. Here, we analyze the possible benefits of having this information, as well as the steps required to collect and process it. The benefits and drawbacks of different sensing technologies are discussed in terms of potential applications, accuracy and cost. We also present the results of preliminary testing using two of the proposed methods. Our analysis indicates that an improved scope for mapping and controlling machine movement is the main benefit that is directly related to the conduct of forestry operations. In addition, there are important indirect benefits relating to ecological mapping. Our analysis suggests that both of these benefits can be realized by measuring the angles of crane joints or the locations of crane segments and using the resulting information to compute the head's position. In keeping with our findings, two companies have recently introduced sensor equipped crane solutions.
Place, publisher, year, edition, pages
Zagreb, Croatia: Croatian Journal of Forest Engineering , 2015. Vol. 36, no 2, 147-164 p.
boom tip control, automation, ALS, sensors, harvester data
Forest Science Robotics Computer Vision and Robotics (Autonomous Systems)
Research subject Computer and Information Science
IdentifiersURN: urn:nbn:se:umu:diva-109881ISI: 000363907900001OAI: oai:DiVA.org:umu-109881DiVA: diva2:859726