Cluster-level robot with soft gripper picks blueberries gently and selectively
CLASP: A Cluster-Level Autonomous Selective Picking Robot with a Soft Rolling-Band Gripper for Fresh-Market Blueberry Harvesting
Robotics
Summary
Picking fresh blueberries gently is hard and takes a lot of work because the fruit is delicate and grows in tight clusters. The authors built a robot called CLASP that picks whole clusters of ripe blueberries without hurting unripe ones. It uses a special soft gripper that rolls around the cluster and carefully pulls off only the ripe berries. Cameras help the robot find and target the right clusters to pick. Testing showed the robot successfully picked most clusters while protecting the fruit, and it could be cost-effective for blueberry farms.
What this means in practice
- •For fruit farm operators: Use a robotic picker to harvest ripe blueberry clusters selectively without bruising, reducing labor costs and improving fresh market quality.$Commercial implications: Enables sale of automated blueberry harvesting robots that pick selectively and gently for fresh-market quality farms.
- •For agricultural robotics engineers: Design and build cluster-level picking robots using rolling-band soft grippers and combined global-local vision for delicate fruit harvesting.
Authors
Yixuan Xia, Yilin Cai, Natalia Belen Espinoza, Changying Li, Zilfina Rubio Ames, Xin Zhang, Yue Chen
Abstract
Fresh-market blueberries require selective, gentle picking, which is labor-intensive and expensive. Over-the-row machine harvesters are fast but non-selective, bruising mixed-ripeness fruit and limiting yield to the processing market. Selective robotic harvesters typically target individual fruits rather than fruit clusters, which limits harvesting efficiency for small, densely clustered blueberries. This paper presents CLASP, a Cluster-Level Autonomous Selective Picking robot with a Soft Active Rolling-Band Gripper (SARB-Gripper). Two compliant bands envelop the cluster and roll against the fruit, drawing mature berries off in sequence, while closed-loop regulation of the pulling force keeps the applied load below the immature detachment threshold. A global-to-local perception pipeline pairs an eye-to-hand camera for global cluster detection and target selection with an eye-in-hand camera for local localization and cluster orientation estimation. Field measurements confirm a clear detachment-force separation between mature and immature fruit, and the SARB-Gripper reproduces a commanded pulling force to within \SI{3.7}{\percent}, enabling selective harvesting at the cluster level. In end-to-end field trials, CLASP autonomously grasped 23 of 25 presented clusters (\SI{92}{\percent}). With the component cost of approximately \$3326 per unit, CLASP offers a scalable approach to selective cluster-level harvesting for fresh-market blueberries.