Can one compact robot automate weeding, spraying and seeding? The robot’s AI vision, autonomous navigation and modular attachments can simplify routine farm operations.
Pragyanik AI is developing the Avighna X1 Lite, an autonomous farm robot designed to perform weeding, targeted spraying, seeding and granular fertiliser application. The prototype combines AI-powered vision, navigation technologies and interchangeable attachments to help small- and medium-scale Indian farmers automate routine fieldwork amid labour shortages and rising operating costs.
The robot uses AI-powered vision to identify weeds and support precision spraying, potentially reducing unnecessary chemical application compared with spraying entire fields. Its navigation system combines the Global Navigation Satellite System (GNSS) with Real-Time Kinematic (RTK) positioning, while LiDAR assists with navigation and obstacle detection. Together, these technologies are intended to help the machine move through fields and perform agricultural tasks with less manual intervention.
Avighna X1 Lite features a four-wheel-drive (4×4) traction system and a compact frame measuring 3 × 2 feet. Its footprint is intended to make it suitable for smaller farms and narrow crop rows where larger agricultural machinery may be difficult to manoeuvre. The working width and ground clearance can also be adjusted to accommodate different crop spacing and field conditions.
The battery-powered robot has a payload capacity of 100–150 kg and reportedly offers eight to 10 hours of runtime on a single charge. It also supports solar-assisted charging, providing an additional charging option for field operations.
The platform uses modular attachments to support weeding, targeted spraying, seeding and granular fertiliser application. This allows the same machine to be configured for different tasks instead of requiring separate equipment for each operation. For smaller farms, consolidating multiple functions into one platform could help reduce equipment requirements and manual effort.
