Mamut agritech robot captures crop data autonomously

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Cambridge Consultants has developed an autonomous four-wheeled robot called Mamut that captures data on individual crop health and overall yield.

The robot’s sensor suite includes stereo cameras, LIDAR, an inertial measurement unit (IMU), a compass, wheel odometers and an onboard AI system that collates all of the input data. This combination of technologies allows Mamut to navigate autonomously and map unstructured environments (simultaneous localisation and mapping, or SLAM) without the need for GPS or the fixed radio infrastructure used by other agritech systems.

According to Cambridge Consultants, automating the capture of crop data from the field provides farmers with more reliable and actionable information, improving efficiency and increasing yields. Data capture on a mass scale is largely undertaken by drones, but this method can lack accuracy for many crops that are hidden beneath a canopy. Autonomously travelling through fields allows Mamut to inspect and analyse individual crops from close range.

“Mamut is a practical application of AI, meeting a real and pressing need, particularly for growers of specialty crops where failure carries a high cost,” said Niall Mottram, head of Agritech at Cambridge Consultants.

“AI systems are already being used to understand crop conditions, yield predictions and to enable weed identification, but our autonomous robotic platform can collect valuable and granular data below the canopy, where drones cannot see. This data enables farmers to treat each plant in their vineyard, orchard or field individually, and on the scale of massive industrial farming, optimising yields and producing more output with less input.”

Mamut’s SLAM capability, allowing the platform to react and learn from unstructured routes in real time, was developed in navigation trials through the twists and turns of a 12-acre maize maze at Skylark Garden Centre, and also at Mackleapple’s orchard. Both facilities are located in Cambridgeshire.