FruitTouch: A Perceptive Gripper for Gentle and Scalable Fruit Harvesting
Abstract
The automation of fruit harvesting has gained increasing significance in response to rising labor shortages. A sensorized gripper is a key component of this process, which must be compact enough for confined spaces, able to stably grasp diverse fruits, and provide reliable feedback on fruit condition for efficient harvesting. To address this need, we propose FruitTouch, a compact gripper that integrates high-resolution, vision-based tactile sensing through an optimized optical design. This configuration accommodates a wide range of fruit sizes while maintaining low cost and mechanical simplicity. Tactile images captured by an embedded camera provide rich information for real-time force estimation, slip detection, and softness prediction. We validate the gripper in real-world cherry tomato harvesting experiments, demonstrating robust grasp stability, effective damage prevention, and adaptability to challenging agricultural conditions.
Demonstration of the FruitTouch gripper harvesting cherry tomatoes. The hardware design is optimized for compactness, low cost, and scalability, while the perception system measures high-resolution contact geometry, 3D force, slip, and object softness. Together, the design integrates mechanical efficiency with rich tactile sensing to enable reliable and efficient fruit harvesting.
Mechanical and Optical Design of FruitTouch Gripper. (A) Mechanical Design. The gripper components are designed for scalability, enabling harvesting of fruits with varying sizes. We use gear-and-rack mechanism to provide actuation. Each finger consists of a soft silicone sensing surface supported by a transparent acrylic sheet, with three LED strips ensuring uniform illumination. A centrally mounted camera, in combination with mirrors, provides comprehensive coverage of both sensing surfaces. (B) Optical Design for the fingertip tactile sensors. The mirror configuration is optimized to maximize the sensing area while maintaining low distortion across different finger distances. Simulated outputs are shown for both the open and closed states of the gripper.
Flow diagram of harvest experiment that includes berry detection, initial pose calculation, and picking phases. (A) Use the RGB-D camera to scan the area and identifying berries. \textbf{(B)} Align and move the manipulator to initial pose. (C) The gripper executes the picking action according to the chosen control strategy.
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BibTeX
@article{FruitTouch2025,
title={FruitTouch: A Perceptive Gripper for Gentle and Scalable Fruit Harvesting},
author={Ruohan Zhang, Mohammad Amin Mirzaee and Wenzhen Yuan},
journal={Under Review},
year={2025},
url={https://rhzhang-ustc.github.io/miniG-project}
}