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.


Group members

Latest publications

Model predictive control for a multiple injection combustion model

Hoang Nguyen Khac, Amin Modabberian, Xiaoguo Storm, Kai Zenger, Jari Hyvönen 2021 Open Engineering

Cashew Trees Detection And Yield Analysis Using UAV-Based Map

Sadouanouan Malo, Thierry Roger Bayala, Issouf Ouattara, Arto Visala 2021 2021 16th Iberian Conference on Information Systems and Technologies (CISTI)

Puu- ja savipohjaisten rakennusmateriaalien ominaisuuksia ja sisäilmaemissioiden on-line havaintoja

Mirja Salkinoja-Salonen, Salla Venäläinen, Timo Hokkanen, Vesa T. Korhonen, Arto Visala, Panu Harmo, Juha Vinha 2021 Rakennusfysiikka 2021 (26.-28.10.2021, Tampere) : uusimmat tutkimustulokset ja hyvät käytännön ratkaisut. Vol. 1

Shipborne sea-ice field mapping using a LiDAR


Model-based on-board post-injection control development for marine diesel engine

Xiaoguo Storm, Hoang Khac Nguyen, Amin Modabberian, Kai Zenger, Jari Hyvönen 2021 Open Engineering

Full-scale measurement of ship performance and ice loads in Antarctic floe ice fields

Fang Li, Muhammad Bilal Khawar, Andrei Sandru, Liangliang Lu, Mikko Suominen, Pentti Kujala 2021 Proceedings of the 26th International Conference on Port and Ocean Engineering under Arctic Conditions, POAC 2021

A Complete Process For Shipborne Sea-Ice Field Analysis Using Machine Vision

Andrei Sandru, Heikki Hyyti, Arto Visala, Pentti Kujala 2020 IFAC-PapersOnLine

RAAS White Paper: Safety Challenges of Autonomous Mobile Systems in Dynamic Unstructured Environments

Mika Vainio, Laura Ruotsalainen, Osiris Valdez Banda, Juha Roning, Jukka Laitinen, Jani Boutellier, Sami Koskinen, Pertti Peussa, Ahm Shamsuzzoha, Ahmad BahooToroody, Vadim Kramar, Arto Visala, Reza Ghabcheloo, Kalevi Huhtala, Rathan Alagirisamy 2020

Optical flow in deep visual tracking

Mikko Vihlman, Arto Visala 2020 Proceedings of the AAAI Conference on Artificial Intelligence

Drone based Mapping and Identification of Young Spruce Stand for Semiautonomous Cleaning

Issouf Ouattara, Heikki Hyyti, Arto Visala 2020 IFAC-PapersOnLine
More information on our research in the Research database.
Research database
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