Innovation project: Environment detection system for harvesting machinery
Harvesting machines have to work in a continuously changing environment. Different conditions, such as the density of the crop being harvested and ground properties, require individual adjustments to machinery settings. Moreover, the driver faces the risk of collision due to the restricted view. This not only leads to machinery damage and consequently to expensive downtime, but also constitutes a hazard to people. Automatic environment detection can optimize machine settings as well as ensuring the safety of the working area.
The aim of the innovation project is to develop a networked sensor system to electronically detect the environment of harvesting machinery. This should enable them to adapt their operation optimally to field conditions. Moreover, in the future they will be able to identify any obstacles and collision risks as well as autonomously taking steps to avoid damage.
This involves recording and analyzing the different properties of the harvesting environment, such as density and obstacles. The information is then used to select appropriate sensors for environment detection, and to develop signal processing algorithms. Real-time networking of the sensors and algorithms with the vehicle control system make it possible for sensor data to be collated and analyzed automatically, so that the machine settings can be autonomously adjusted and collisions with obstacles can be avoided. The project draws on the results of cross-sectional projects in self-optimization, human-machine interaction and intelligent networking. The networked sensor system will be validated by a demonstration model and extensive field tests, and then integrated into a harvesting machine.
This innovation project will increase the efficiency and safety of agricultural machinery – with equal or improved harvest quality. Damage to people and machinery will be minimized and downtime reduced. The sensor system can also be used for other application purposes, such as unmanned container transporters in shipping ports, or in autonomous multi-robot systems.
01 July 2014 - 30 June 2017