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Articles by Magnus Karlberg

Category : Research article

article id 1386, category Research article
Håkan Lideskog, Magnus Karlberg. (2016). Simulated continuous mounding improvements through ideal machine vision and control. Silva Fennica vol. 50 no. 2 article id 1386. https://doi.org/10.14214/sf.1386
Keywords: site preparation; silviculture; remote sensing; scarification; clearcut obstacles; mounding simulation; work procedures
Highlights: Different strategies for how to utilise machine vision to streamline the mounding head movements were developed and evaluated; The theoretical minimum rate of encountered obstacles while utilising machine vision in continuous mounding is presented, provided that an optimal continuous mounding has been performed; The needed minimum resolution of a machine vision system at work on a clearcut area was found.
Abstract | Full text in HTML | Full text in PDF | Author Info

To promote the growth and survival of regenerated forests, site preparation prior to tree planting on clearcuts is necessary. This is often performed with scarifiers, either through trenching or mounding. Mounding is generally considered better in a plant survival perspective but is inefficient on obstacle-rich clearcuts. By utilising machine vision through e.g. remote sensing methods, new strategies can enable efficient mound positioning. In this paper, three realistic strategies utilizing ideal clearcut object identification through machine vision have been developed that can be used for more efficient mounding. The results show that mounding efficiency can be significantly improved with a new mound positioning strategy that employs ideal object identification, especially on obstacle-rich clearcuts.

 

 

  • Lideskog, Luleå University of Technology, Department of Engineering Sciences and Mathematics, Division of Product and Production Development, SE-971 87 Luleå, Sweden E-mail: hakan.lideskog@ltu.se (email)
  • Karlberg, Luleå University of Technology, Department of Engineering Sciences and Mathematics, Division of Product and Production Development, SE-971 87 Luleå, Sweden E-mail: magnus.karlberg@ltu.se

Category : Research note

article id 1136, category Research note
Håkan Lideskog, Back Tomas Ersson, Urban Bergsten, Magnus Karlberg. (2014). Determining boreal clearcut object properties and characteristics for identification purposes. Silva Fennica vol. 48 no. 3 article id 1136. https://doi.org/10.14214/sf.1136
Keywords: forestry; forest regeneration; clearcut obstacles; terrain description; terrain conditions; site properties
Highlights: We define the quantitative properties and qualitative characteristics of stumps, stones, slash, and roots, the most important objects interacting with machine activities after clearcutting; We develop a flowchart showing how a computer-aided system using clearcut object identification should be executed.
Abstract | Full text in HTML | Full text in PDF | Author Info
After clearcutting, machines traffic the clearcut conducting different silvicultural activities. Many objects on a forest clearcut (slash residues, stones, stumps and roots) may disturb e.g. site preparation and planting. This paper describes properties and characteristics of these objects. A flowchart was developed that describes a possible computer-aided system that identifies the objects, and ultimately, makes a machine avoid or target them. A system for obstacle identification creates conditions for further technical development and (semi)automation of e.g., site preparation, mechanized planting, and stump removal.
  • Lideskog, Division of Product and Production Development, Luleå University of Technology, SE-97187 Luleå, Sweden E-mail: hakan.lideskog@ltu.se (email)
  • Ersson, Department of Forest Biomaterials and Technology, SLU, SE-90183 Umeå, Sweden E-mail: back.tomas.ersson@slu.se
  • Bergsten, Department of Forest Biomaterials and Technology, SLU, SE-90183 Umeå, Sweden E-mail: urban.bergsten@slu.se
  • Karlberg, Division of Product and Production Development, Luleå University of Technology, SE-97187 Luleå, Sweden E-mail: magnus.karlberg@ltu.se

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