VALD
The overarching goal is to automate the short cycle loading for improved driver support in products offered at the market today, as well as autonomous operation of next-generation unmanned machines.
To accomplish this the focus will be on neural network models and machine learning (ML) with frame-based camera vision to capture environmental aspects and properties. The expected results from the VALD project will develop the entire control and navigation path of the short loading cycle.
The results will be used by the cooperation partner, Volvo, in order to strengthen the capabilities to develop and test new functions for driver support, teleoperated, semi-autonomous, and fully autonomous wheel-loaders. The capability and capacity to introduce functions based on machine learning (ML) and camera vision will be strengthened through the company´s increased knowledge and the development of new prototype solutions. These functions are expected to contribute to making the journey towards fully autonomous load carriers that can operate efficiently in heavy construction environments.
Coordinator: Luleå University of Technology - Department of Computer Science, Electrical and Space Engineering
Funder: Vinnova
Duration: May 2022 - May 2024
Contact
Ulf Bodin
- Professor
- 0920-493036
- ulf.bodin@ltu.se
- Ulf Bodin
Updated: