Biologically inspired robotic perception-action for soft fruit harvesting in vertical growing environments.

ABSTRACT: Multiple interlinked factors like demographics, migration patterns, and economics are presently leading to the critical shortage of labour available for low-skilled, physically demanding tasks like soft fruit harvesting. This paper presents a biomimetic robotic solution covering the full 'Perception-Action' loop targeting harvesting of strawberries in a state-of-the-art vertical growing environment. The novelty emerges from both dealing with crop/environment variance as well as configuring the robot action system to deal with a range of runtime task constraints. Unlike the commonly used deep neural networks, the proposed perception system uses conditional Generative Adversarial Networks to identify the ripe fruit using synthetic data. The network can effectively train the synthetic data us

SUBMITTER: Wang F 

PROVIDER: S-EPMC10010232 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature