RoMu4o is a ground robot equipped with a 6‑DOF arm and a vision system that performs real‑time deep‑learning image processing and motion planning for proximal hyperspectral leaf sensing in orchards. The system uses robust perception and manipulation pipelines to identify leaf 3D structure, propose 6‑D poses, and generate collision‑free, constraint‑aware paths for precise leaf grasping and spectroscopy. In lab trials the robot achieved a 95 % success rate for 1‑LPB hyperspectral sampling, while field trials in a pistachio orchard reached 70 % success for autonomous leaf grasping and measurement.
whyItMatters":"The system demonstrates a viable robotic solution to automate leaf‑level hyperspectral sensing, addressing labor shortages and enabling precise crop health monitoring in precision agriculture."
By Mehrad Mortazavi, David J. Cappelleri, Reza Ehsani
Plant root phenotyping is fundamental to understanding below-ground structures, optimizing crop management, and improving agricultural sustainability. This paper presents a multimodal robotic AI framework that integrates 3D skeleton extraction with language-guided reasoning for interpretable and data-efficient root analysis.
3D plant phenotyping is notoriously known to be procedure-complicated and of low throughput due to the extensive multi-view imaging, the fragile 3D reconstruction pipeline, and the additional cost from reconstructed geometry to phenotypic extraction. These limitations are further amplified in low-cost data acquisition, where smartphone videos or sparsely sampled multi-view images provide limited view overlap and self-occlusion.
arXiv:2609.13606v1 Announce Type: cross
Abstract: Multi-arm robotic harvesting offers a promising path to improve harvesting efficiency and reduce reliance on manual labor. However, practical deploym...
By Vrishan Inukollu, Adyan Zaman, Anvi Kudaraya, Carlos Lazcano, Yuankai Zhu, Stavros Vougioukas, Xiaofan Yu
arXiv:2609.21059v1 Announce Type: cross
Abstract: Plant growth and agricultural production form the foundation of a country's sustainable development and directly impact human livelihoods. Recent adv...
By Longchao Da, Xiaoou Liu, Xingjian Li, Lirong Xiang, Hua Wei
arXiv:2603. 07866v3 Announce Type: replace-cross Abstract: Offshore inspection and maintenance have increasingly been using legged robots for routine sensing, yet many useful interventions still require physical interaction with tools, containers, and task-relevant objects.
By Dilermando Almeida, Juliano Negri, Guilherme Lazzarini, Thiago H. Segreto, Ranulfo Bezerra, Gustavo J. G. Lahr, Ricardo V. Godoy, Marcelo Becker