Sustainable farming comes with a responsibility that is self regulated by farmers. We believe in empowering the farmers of today and tomorrow with
To accomplish this we have 2 goals:
. Increase productivity of a tractor from 8 hour day to 16+ hour day
. Make farming easy and adaptable for young farmers driven by connected devices
Empower existing fleets with autonomous technology , an easy-to-use platform, and end-to-end service ranging from perception to machine control.
IoT device on wheels with technology as value driver,driven by adoption of alternative fuels.
management and planning of a field, equipment and fieldwork for maintenance and maximum efficiency.
AI & Robotics offer the opportunity to improve efficiencies on the farm.
Our retrofit kit for navigation and machine control leverage Artificial Intelligence (AI) for human-like scene understanding.
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Our retrofit kit for navigation and machine control leverage Artificial Intelligence (AI) for human-like scene understanding.
A full surround camera setup is the basis for reasoning about 3D objects , farm layout and the automated navigation movements in-row and at the headland.
Our state-of-art algorithms allows for seamless integration of multiple sensors into a centimeter accurate high-fidelity representation of the fields and planning trajectories even at night and in poor visibility.
Many farmers expect their vehicles to be fully integrated into their digital lives.
Our software defined vehicles are equipped with powerful hardware and software,can communicate with its environment, collect data in real-time operation, and send it to the cloud for digitalization , automation.
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Our software defined vehicles are equipped with powerful hardware and software,can communicate with its environment, collect data in real-time operation, and send it to the cloud for digitalization , automation.
We use Modular design , automotive sensors and ML-optimised compute platforms for our next generation autonomous vehicles. This allows us to offer a scalable solution which enables for large scale fleet learning in the future.