Towards In-Field Phenotyping Exploiting Differentiable Rendering with Self-Consistency Loss
Federico Magistri Nived Chebrolu Jens Behley Cyrill Stachniss Federico Magistri Nived Chebrolu Jens Behley Cyrill Stachniss
In modern agriculture, measuring phenotypic traits helps breeders monitor plant growth, increase yield, and provide food, feed, and fiber. Traditional phenotyping requires intensive manual work, partially being intrusive. In this paper, we investigate the challenge of measuring phenotypic traits in an automated fashion through mobile robots operating in field environments. In particular, we want t...