Picking Point Localization and Path Planning for Hotan Rose Based on a Lightweight Segmentation Model

Abstract

The Hotan rose, a high-value specialty crop cultivated in Xinjiang, exhibits pronouncedly non-uniform flowering phenology, which has historically necessitated labor-intensive manual harvesting. To date, however, no integrated framework has been reported that concurrently addresses lightweight visual perception, precise picking-point localization, and three-dimensional path planning for this specific crop. In this study, we develop L-SOP, an end-to-end continuous picking methodology tailored to the unique requirements of Hotan rose harvesting. At the perception stage, we introduce YOLOv11n-LPD-Seg, a lightweight segmentation model that incorporates a joint compression strategy combining global pruning with channel-wise distillation (CWD). This design improves the mAP@0.5 values for flowers and buds by 0.1 and 0.7 percentage points, respectively. It also reduces the model size from 6.1 MB to 2.4 MB, representing a 60.7% reduction, and decreases the computational cost from 10.2 GFLOPs to 6.8 GFLOPs, representing a 33.3% reduction. For picking point localization, we develop the MGRO-Loc algorithm, which integrates multiple geometric constraints to achieve accurate spatial positioning. The algorithm achieves mean absolute errors of 2.33 mm under indoor conditions and 2.84 mm under outdoor conditions. For path planning, we propose the OG-LKH algorithm, which replaces the conventional orthogonal polyline distance metric with an oblique gate-shaped distance measure and incorporates a multi-start strategy and a gate-aware heuristic search. Compared with the standard LKH algorithm, OG-LKH reduces the average path length by 23.5% while maintaining a computation time of 0.0117 s. Even in high-density scenarios involving 36 waypoints, its computation time is only 0.0387 s on edge-computing devices. These three modules work synergistically to form a complete solution for selective continuous rose picking. The proposed framework can be deployed on edge devices, providing a viable technological pathway toward efficient autonomous harvesting of Hotan rose flower and bud.