ELEC-E8120 - Smart forestry machines, Lecture, 27.2.2023-8.5.2023

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Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

Forest machines are becoming semiautonomous, with modern machine perception and methods of probabilistic robotics and modern control, the efficiency, economy, quality and operability of forest harvesting can be improved. With the same machine perception  the machine are also becoming producers of forest big data, also conservation of valuable nature forest areas and biodiversity can be quaranteed and documented. 

Some lectures will given in the forest faculties of HY  and UEF.

Credits: 5

Schedule: 27.02.2023 - 08.05.2023

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Arto Visala, Pekka Forsman

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    Nordic Cut-to-Lenght forest harvesting and Silviculture; kinematic models of harvester and forwarder; machine vision,  LiDARs and SLAM in forest, creating map of trees (Forestrix-project); machine vision based quality measurements ( Metrix&MetrixPro); automated silviculture of young forests (NeoSilvix), Augmented reality HMIs (COMBAT); positioning in forest, use of drones in forestry, semiautonomous forwarder (Autologger), MPC in the automatic driving in forests.

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Exam and the reports of the two projects above.

    Home exam 65 %,  the two course projects 35%.

Workload

  • valid for whole curriculum period:

    Lectures cover the main content of the course. In addition, the mapping the forest is illustrated in a small LiDAR 3D-point-cloud -project and the automatic driving in forest  is illustrated in a small Polaris eATV-project. Both projects are done in the teams of four students.

    Contact teaching 27 h, independent studies and the two projects 105 h, examination 3 h =  135 h

    Compulsory attendance 3

DETAILS

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    7 Affordable and Clean Energy

    9 Industry, Innovation and Infrastructure

    12 Responsible Production and Consumption

    13 Climate Action

    15 Life on Land

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Spring IV - V
    2023-2024 Spring IV - V

Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof