Abstract:
Strawberries, highly valued both commercially and for consumption, are predominantly cultivated in controlled environments like greenhouses. Despite these advantages, human labor remains a significant factor in strawberry production costs, especially during harvesting. To address this, there is a growing interest in developing strawberry harvesting robots. However, detecting strawberries poses challenges due to leaf shading, overlapping, and plant structure interference. Enhancing the visual object detection system is crucial for accurate and real-time detection. Given the vulnerability of strawberries to damage due to low mechanical strength during harvesting, we propose a stem-based harvesting method and plan to develop an efficient motion planning approach for the robot manipulator [1][2]. The goal is to enable the intelligent robot to navigate autonomously, picking strawberries with improved efficiency and minimal damage, thus transforming strawberry harvesting processes.
