Pomelo fruit-picking robot for unstructured environments
Year: 2024
Type: conference-paper
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.
Authors: Shangshang Cheng, Zhengwei Yu, Zhen Li, Qingru Fan, Shilei Lyu, Wei Wen, Zhou Yang
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4405285724