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    • Keskustelualue icon
      Announcements Keskustelualue
    • Kansio icon
      Lecture 1, Feb 26 & Mar 4: Arrangements, Current CTL Forest Machines, Harvester + Forwarder Kansio

      Arrangements

      • Lectures: Arto.Visala@aalto.fi on Mondays in the beginning (maybe also on Wednesday later) 12:15- 12:00 TU4
      • Lectures cover the main content of the course.
      • The automatic driving in forest is illustrated in a small Polaris eATV-project, done individually.
      • Exam or 7 x Study Diaries 65 % and the report of the project above 35%.
      • Study Diary is a one A4 page summary about each lecture set, written by hand. Take a photo, convert it to pdf and sent arto.visala@aalto.fi.

      Current CTL Forest Machines, Harvester + Forwarder

      • The best way to learn the state of art current forest machines to look at www-pages of the leading
      companies. Videos illustrate the operation. Look particularly what is represented about control systems and harvesting information systems.
      • Smart machines means semiautonomous operations in easy conditions and that the machines with modern perception devices are becoming producers of big data. 

      https://www.ponsse.com/#/
      https://www.deere.com/en/forestry-and-logging/cut-to-length-logging/

    • Kansio icon
      Lecture 2, Mar 11: Forest SLAM with LiDAR, Localizationg and Mapping Kansio
      Saatavilla vasta, kun: Kuulut ryhmään L01 (SISU)

      Forest SLAM with LiDAR, Localizationg and Mapping
      Positioning in forest, Forest SLAM with LiDAR, creating map of trees. Experiments with ATV , IEEE ICRA 2007. Also experiments with a real Forestry machine

      First 3D Forest SLAM
      Feature Based Modeling and Mapping of Tree Trunks and Natural Terrain Using 3D Laser Scanner Measurement System, IFAC IAV 2013

    • Kansio icon
      Lecture 3, March 18: Machine Vision in Forest SLAM Kansio
      Saatavilla vasta, kun: Kuulut ryhmään L01 (SISU)

      Machine Vision in Forest SLAM
      Measuring diameters of the stems of trees (Kosti Kangas)
      Classification of species of trees (Sampsa Kosonen)

    • Kansio icon
      Lecture 4, March 2024: Machine perception in the harvester head Kansio
      Saatavilla vasta, kun: Kuulut ryhmään L01 (SISU)

      Machine perception in the harvester head

      BEFORE FELLING – MEASUREMENTS
      • MOTION VISION, DEPTH IMAGE FROM OPTICAL FLOW
      • BEFORE FELLING – MEASUREMENTS, STEREO VISION
      • BEFORE FELLING – MEASUREMENTS, LiDAR
      DURING PROCESSING -METHODS
      • DURING PROCESSING –Fiber optic blade camera, VTT
      • DURING PROCESSING –CUT SURFACE IMAGE ANALYSIS , TTY Prof Ritala
      •  Lenght measurement using sequence of images


    • Kansio icon
      Lecture 5, April 8: Semiautonomous Cleaning of Young Forests Kansio
      Saatavilla vasta, kun: Kuulut ryhmään L01 (SISU)

      Semiautonomous Cleaning of Young Forests
      • The prototype of a Semiautonomous Early Cleaning machine
      • The Instrumentation of the crane
      • Recognition of small trees with machine vision
      • HMI
      • Detection, Localization and Species Identification of Young Trees Using Machine Vision fro late cleaning

    • Kansio icon
      Lecture 6, April 22: Nonlinear Model Predictive Control (NMPC) of the Forestry Crane Kansio
      Saatavilla vasta, kun: Kuulut ryhmään L01 (SISU)
      Nonlinear Model Predictive Control (NMPC) of The Forestry Crane
      • The general structure of the NMPC problem
      • Kinematic model of the crane
      • NMPC for boom tip control with Anti-Sway
      Sway Estimation using Inertial Measurement Units for Cranes with a Rotating Tool
    • Kansio icon
      Lecture 7, April 29: Automatic driving in terrain, semiautonomous forwarder Kansio
      Saatavilla vasta, kun: Kuulut ryhmään L01 (SISU)

      Automatic driving in terrain, semiautonomous forwarder

      Introduction of project SUSTAINABLE AND COST-EFFICIENT SEMI-AUTONOMOUS FOREST MACHINE SYSTEM FOR THE CLIMATE CHANGE CHALLENGED FUTURE, AUTOLOGGER

      Positioning, Map of trees, Forest SLAM

      Dynamic models for the three test platforms

      Measuring the 3Dform of the driving path

      MPC-control for Automatic driving