Leveraging 5G private networks, UAVs and robots to detect and combat broad-leaved dock (Rumex obtusifolius) in feed production

TL;DR

This paper presents an autonomous system utilizing 5G-connected UAVs and robots with AI detection to identify and precisely spray Rumex obtusifolius in grasslands, enhancing weed control for livestock feed production.

Contribution

It introduces an integrated system combining UAVs, autonomous sprayers, 5G connectivity, and AI for targeted weed detection and eradication, with real-world operational testing.

Findings

UAVs and robots are operational and integrated with 5G networks.

AI detection algorithm is under training and improving.

System demonstrates potential for precise, automated weed control.

Abstract

In this paper an autonomous system to detect and combat Rumex obtusifolius leveraging autonomous unmanned aerial vehicles (UAV), small autonomous sprayer robots and 5G SA connectivity is presented. Rumex obtusifolius is a plant found on grassland that drains nutrients from surrounding plants and has lower nutritive value than the surrounding grass. High concentrations of it have to be combated in order to use the grass as feed for livestock. One or more UAV are controlled through 5G to survey the current working area and send back high-definition photos of the ground to an edge cloud server. There an AI algorithm using neural networks detects the Rumex obtusifolius and calculates its position using the UAVs position data. When plants are detected an optimal path is calculated and sent via 5G to the sprayer robot to get to them in minimal time. It will then move to the position of the broad-leafed dock and use an on-board camera and the edge cloud to verify the position of the plant and precisely spray crop protection only where the target plant is. The spraying robot and UAV are already operational, the training of the detection algorithm is still ongoing. The described system is being tested with a fixed private 5G SA network and a nomadic 5G SA network as public cellular networks are not performant enough in regards to low latency and upload bandwidth.