Department of Electrical Engineering and Automation

Autonomous systems

Autonomous systems group has been conducting hands-on research on physical heavy-duty semi-autonomous machines and autonomous mobiles robots, mainly in agriculture and forestry, for more than two decades. The group specializes in situational awareness, machine perception, SLAM, path planning, navigation, model predictive control, and multi-robot systems related issues in dynamic environments.
Autonomous systems Group

For forest harvesters, a perception system that is capable of forest SLAM, i.e. mapping the trees and localizing the machine, has been developed. The group has developed different utilizing schemes for the tree map information. Stereo vision and image sequence analysis, i.e. motion vision, have an important role in these developments.

Robotization of silvicultural machines has been studied. The aim is to recognize the young trees that should be left to grow, and other trees that can be cut down, with the help of machine vision and laser scanners, as well as instrumentation and automatic motion control of the forestry boom. The developments have been tested with real machines.

For agricultural tractor and implement combinations, several prototypes of ISOBUS networked (ISO 11783) control systems for implements have been realized, in which automatic GPS based precision agriculture, semiautomatic integrated control and control system development have been studied and demonstrated. Path planning, automatic navigation and model predictive control path tracking have been developed.

Several small agricultural field robots have been built in student projects, which have participated in European Field Robot Event contest. A full-scale agricultural field robot is used to study online path planning.

The group is led by Professor Arto Visala.

Projects

Latest publications

Modeling the end-use performance of alternative fuels in light-duty vehicles

Yuri Kroyan, Michal Wojcieszyk, Ossi Kaario, Martti Larmi, Kai Zenger 2020 Energy

Operational Profile Based Optimization Method for Maritime Diesel Engines

Hoang Nguyen Khac, Kai Zenger, Xiaoguo Storm, Jari Hyvönen 2020 Energies

Modeling the Impact of Alternative Fuel Properties on Light Vehicle Engine Performance and Greenhouse Gases Emissions

Yuri Kroyan, Michal Wojcieszyk, Martti Larmi, Ossi Kaario, Kai Zenger 2019 SAE Technical Papers

Internet of things for indoor air quality measurements

Janne Luukkaa, Arto Visala, Panu Harmo, Mirja Salkinoja-Salonen 2019 Proceedings of the 17th IEEE International Conference on Industrial Informatics, INDIN 2019

Development of Working Life Competencies in a Project Course for Master Students at Aalto University

Robert Millar, Kirsti Keltikangas, Paulo Pinho, Vesa Vuorinen, Pekka Forsman, Anouar Belahcen, Jorma Kyyrä 2019 YLIOPISTOPEDAGOGIIKKA

Designing optimal control maps for diesel engines for high efficiency and emission reduction

Hoang Nguyen Khac, Kai Zenger 2019 Proceedings of the 18th European Control Conference, ECC 2019

Optimal control maps for fuel efficiency and emissions reduction in maritime diesel engines

Hoang Nguyen Khac, Kai Zenger, Xiaoguo Storm, Jari Hyvönen 2019 Integrated Energy Solutions to Smart And Green Shipping

Sähkökemiallisten antureiden ja fysikokemiallisten mittaustekniikoiden avulla uutta tietoa sisäilman altisteista

Jorma Selkäinaho, Panu Harmo, Arto Visala, Mirja Salkinoja-Salonen, Veli-Matti Niiranen, Vesa T. Korhonen, Janne Luukkaa, Heli M. Sirén, Markus O. Lehtonen, Marja-Liisa Riekkola, Heidi Salonen, Maria A. Andersson, Raimo Mikkola, Jarek Kurnitski, Elisa Aattela 2019 Sisäilmastoseminaari 2019
More information on our research in the Research database.
Research database
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