Autonomous Crop Row Guidance Using Adaptive Multi-ROI in Strawberry Fields.

ABSTRACT: Automated robotic platforms are an important part of precision agriculture solutions for sustainable food production. Agri-robots require robust and accurate guidance systems in order to navigate between crops and to and from their base station. Onboard sensors such as machine vision cameras offer a flexible guidance alternative to more expensive solutions for structured environments such as scanning lidar or RTK-GNSS. The main challenges for visual crop row guidance are the dramatic differences in appearance of crops between farms and throughout the season and the variations in crop spacing and contours of the crop rows. Here we present a visual guidance pipeline for an agri-robot operating in strawberry fields in Norway that is based on semantic segmentation with a convolution neural net

SUBMITTER: Ponnambalam VR 

PROVIDER: S-EPMC7571079 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature