Pomelo fruit-picking robot for unstructured environments

Abstract The adoption of mechanized and intelligent harvesting equipment is an effective approach to enhancing the stability and competitiveness of the pomelo industry. This study presents the development of a harvesting device tailored for pomelos by improving target recognition algorithms and optimizing the picking mechanism. A fruit stem posture fitting algorithm based on the morphological characteristics of pomelos was developed, capable of obtaining spatial information on fruit stems even in obstructed environments. A serial PPRP picking mechanism with a fault-tolerant end-effector was designed, and kinematic equations and control theory models were established. Experimental results demonstrate that the workspace of the designed robotic arm for pomelo harvesting has a height of 1.9 meters and a depth of 1.3 meters, with a recognition accuracy of 94% and a picking success rate of 72%. The harvesting efficiency reached two fruits per minute, making the device suitable for operations in both structured and unstructured orchard environments.