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Machines 12 00642 by nopa is a document available to read on EtoBox.

This study presents deep learning-based methods for enhancing 6D pose estimation and multi-mode tracking in citrus-harvesting robots, addressing challenges in agricultural automation. It introduces a dataset named HWANGMOD, developed from both virtual and real environments, and proposes algorithms for ripeness classification and optimal harvest sequencing. Experimental results demonstrate the effectiveness of the EfficientPose model in achieving high accuracy and real-time processing, contributing to the co

Author

nopa

Language

EN