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

Group members

Latest publications

More information on our research in the Research database.
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