AgriEngineering, Volume 7, Issue 12
2025 December - 40 articles
Cover Story: This paper presents a mobile fruit-harvesting robot capable of autonomously deciding where to move and how to pick by leveraging a reachability map and an inverse reachability map. Fruits are first detected and localized in 3D using a YOLOv5 RGB-D vision system with precise hand–eye calibration. The robot then evaluates whether each fruit is safely reachable by combining reachability, manipulability, and task-oriented “harvestability” indices into a unified score. For fruits deemed unreachable, the inverse map recommends an optimal base pose that maximizes the number of fruits fruits that can be harvested per repositioning. The complete system is implemented in ROS 2 and validated in a virtual orchard, demonstrating improved picking success, reduced unnecessary motion, and a practical pathway toward scalable, autonomous harvesting in real agricultural environments. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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