Autonomous machines can reduce risks and increase efficiency in agriculture

Self-driving agricultural vehicles can make heavy and hazardous farming tasks both safer and more sustainable. New research shows that automated vehicles can reduce driving distance by up to 30 percent during the collection of silage bales, while also improving working conditions and reducing environmental impact.

"By allowing machines to drive and plan their routes autonomously, we can reduce both accident risks and the workload for humans," says Saira Latif, Doctoral Student in Machine Design at Luleå University of Technology.

Handling large quantities of forage in the field is one of agriculture’s most demanding tasks. Heavy silage bales can weigh up to 800 kilograms and require vehicles such as tractors or loaders operated by humans, often under working conditions associated with physical strain and safety risks. In her research, Saira Latif has developed a system that enables agricultural vehicles to plan their paths and navigate independently when collecting so-called Big Bales, a task that is otherwise both time-consuming and potentially dangerous.

"The goal has been to develop solutions that can improve safety while making farm work more efficient, especially for smaller farms with limited resources," says Saira Latif.

Saira Latif, Doctoral Student in Machine Design at Luleå University of Technology.

New concept for articulated vehicles

The new technology is based on an innovative articulated crane-vehicle design that can reduce the total driving distance by up to 30 percent during bale collection. This means lower fuel consumption and shorter working time, as well as reduced environmental impact.

To achieve this, Saira Latif has developed improved off-road navigation algorithms for autonomous vehicle control. By using two variants of the so-called pure pursuit steering algorithm, she demonstrated up to 50 percent real-time navigational improvement in unstructured off-road real environments, which enable the vehicle to achieve both higher precision and more stable movement, particularly important in operations where direction and positioning are critical, such as in the collection of silage bales.

"It is not only about driving from point A to point B but about " simultaneously optimizing total driving distance for collection sequence for multiple bales at far away pickup locations corresponding to innovative articulated vehicle’s crane length ". The innovative machine is able to make decisions, adapt to the terrain, plan and navigate in a way that optimizes the entire bale collection process through multi-goal optimized planning. " My work shows the breakthrough real-world proof of concept, for the very first time, for full automation of the bale collection task starting from optimized multi-targets planning to autonomous navigation to autonomous picking and loading of heavy objects in unstructured off-road real environments," says Saira Latif.

Contributing to more efficient production

The autonomous solutions can also be applied in other fields where vehicles operate in challenging terrain, such as forestry. With increased precision, reduced need for human intervention, and improved safety, the technology contributes to more efficient production and a safer working environment.

"My research shows a clear potential for self-driving vehicles in agriculture and other off-road sectors. It is a step towards a smarter and more sustainable agricultural system," says Saira Latif.

• Machine design