In the ever-evolving landscape of agricultural technology, a new frontier is emerging that could revolutionize the way we harvest and haul arable and open-field vegetable crops. Autonomous unmanned transport combinations are stepping into the spotlight, promising to address some of the industry’s most pressing challenges. These challenges include labor shortages, soil compaction, and the need for increased capacity and efficiency.
The agricultural sector has long relied on increasingly large and powerful harvesters to meet the demands of growing acreage and shrinking workable days. This trend has extended to haulage combinations, which have grown in length to boost capacity, albeit at the cost of heightened soil compaction and structural damage risks. However, the tide may be turning with the advent of autonomous transport solutions.
Autonomous unmanned transport combinations could mark a significant turning point by addressing labor shortages while also mitigating soil pressure and compaction. This technology has been explored before, notably in the HWodKa project, which ran from 2005 through 2022. This Dutch initiative focused on autonomous carriers with interchangeable modules for field transport, aiming to reduce soil pressure and enhance logistics. While the project’s ideas were ahead of their time, some elements, such as tyre pressure control and controlled traffic farming, are now in use.
The need for autonomy remains, especially during wet seasons, but the logistics and technology are complex and often expensive. Decoupling field and transport logistics is not always practical, particularly when fields are close to the farm. Additionally, sensitive crops like potatoes and onions may require fewer transfers to minimize damage. Overload trailers are increasingly used during sugar beet harvests, but there is still room for innovation.
Several companies have already developed systems that allow unmanned tractors to follow and be directed by combine harvesters during unloading. Kinze Manufacturing was one of the first to introduce such a system in 2011, although updates have since ceased. Other notable systems include Ag Leader’s CartACE, John Deere’s Machine Sync, PTx Trimble’s OutRun, and Raven’s Cart Automation. These systems are designed to address labor shortages and enhance efficiency, with some already available in various regions and suitable for different combine and tractor models.
In the Netherlands, Marnix van het Hof of Firma Ziengs in Klazienaveen sees autonomous harvest logistics as a potential solution to labor shortages in potato and sugar beet lifting. He envisions a future where unmanned transport units could be controlled by the harvester operator or managed by a single trailer driver overseeing additional unmanned vehicles. However, he acknowledges that the right technical solution for Dutch conditions may not yet exist and expresses curiosity about the potential costs.
Looking beyond agriculture, autonomous transport is already routine in industries like mining and construction. In agriculture, commercial applications include the Burro from Augean Robotics, the Amiga from Farm-ng, the Squirrel from Muddy Machines, the Valera Flex from Ant Robotics, and the MULA 1250 from Spain. These compact autonomous transport vehicles are designed for moving harvested fruit, vegetables, and nuts, often in crates.
The National Fieldlab for Precision Agriculture (NPPL) project in the Netherlands is currently developing a research proposal to adapt these systems to Dutch conditions. The goal is to test existing autonomous systems for on-field grain transport and gain valuable insights for developing solutions suited to Dutch practice. In the coming years, NPPL and Wageningen University & Research (WUR) aim to collaborate with farmers and manufacturers on adapting existing haulage combinations for autonomous operation and developing new solutions. These could include lightweight autonomous harvesting machines and vehicles with extremely low ground pressure, designed for lifting and transporting Dutch root crops with minimal soil impact.