Advancements in AI Driven Perception Systems for Agricultural Robotics

Abstract

Robots have become increasingly important over the years. Ever- increasing demands for production, labour fatigue, reduced labour and environmental safety have brought robotics to the forefront of scientific advances. The same approach is used with agro-robots, where similar solutions are feasible. help farmers farm faster, safer and more profitably This paper evaluates the prevailing level of mind-based vision in agricultural robots and field applications, specifically weed identification, crop identification, classification, disease detection, vision- based navigation, harvesting, and propagation. This paper analyzes the present level of mind-based vision in agricultural robots in field applications, specifically weed recognition, crop identification, phenotyping, disease detection, vision-based navigation, harvesting, and propagation. The survey demonstrated an extensive curiosity in drawing vision-based solutions.in agricultural robotics, where the most popular RGB cameras and sensors optionally can have promising outcomes, and no particular algorithm leads all others. Instead, artificial intelligence gives specific benefits for performing certain issues associated with agriculture.