Manual tissue extraction from potato tubers for molecular pathogen detection is highly laborious. This study presents a machine-vision-guided, dual-arm coordinated inline robotic system integrating tuber grasping and tissue sampling mechanisms. Tubers are transported on a conveyor that halts when a YOLOv11-based vision system detects a tuber within the workspace of a one-prismatic-degree-of-freedom (P-DoF) robotic arm. This arm, equipped with a gripping end-effector, secures and positions the tuber for sampling. The second arm, a 3-P-DoF Cartesian manipulator with a biopsy punch-based end-effector, then performs tissue extraction guided by a YOLOv10-based vision system that identifies the sampling sites on the tuber such as eyes or stolon scars. The sampling involves four stages: insertion of the punch into the tuber, punch rotation for tissue detachment, biopsy punch retraction, and deposition of the tissue core onto a collection site. The system achieved an average positional error of 1.84 mm along the tuber surface and a depth deviation of 1.79 mm from a 7.00 mm target. The success rate for core extraction and deposition was 81.5%, with an average sampling cycle of 10.4 seconds. The total cost of the system components was under
View on arXiv@article{l.g.2025_2505.00774,
title={ Design, Integration, and Evaluation of a Dual-Arm Robotic System for High Throughput Tissue Sampling from Potato Tubers },
author={ Divyanth L.G. and Syed Usama Bin Sabir and Divya Rathore and Lav R. Khot and Chakradhar Mattupalli and Manoj Karkee },
journal={arXiv preprint arXiv:2505.00774},
year={ 2025 }
}