Hybrid Robotic Meta-gripper for Tomato Harvesting: Analysis of Auxetic Structures with Lattice Orientation Variations

2025-10-11

AI Summary

Robotic harvesting of delicate fruits and vegetables remains challenging due to the difficulty of achieving compliant, stable grasping in unstructured, fragile environments. Method: This study proposes a rigid–soft hybrid six-finger tomato harvesting gripper integrating auxetic (negative Poisson’s ratio) metamaterial lattice structures. A systematic experimental and modeling framework—combining digital image correlation (DIC) with nonlinear finite element analysis (FEA)—is established to characterize coupled mechanical behavior. Contribution/Results: For the first time, the quantitative influence of lattice orientation (0°–60°) on gripper compliance, contact force distribution, and motor torque is revealed. The co-design framework enables concurrent optimization of mechanical response and energy efficiency. Experimental validation using 3D-printed prototypes demonstrates that an optimized orientation configuration reduces fruit damage rate by 23.6% and peak motor torque by 31.4%, significantly enhancing harvesting reliability and energy efficiency in automated systems.

Technology Category

• Intelligent Robots: Manipulation
• Search and Optimization: Mixed Discrete/Continuous Search
• Computer Vision: Biometrics, Face, Gesture & Pose

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

The agricultural sector is rapidly evolving to meet growing global food demands, yet tasks like fruit and vegetable handling remain labor-intensive, causing inefficiencies and post-harvest losses. Automation, particularly selective harvesting, offers a viable solution, with soft robotics emerging as a key enabler. This study introduces a novel hybrid gripper for tomato harvesting, incorporating a rigid outer frame with a soft auxetic internal lattice. The six-finger, 3D caging-effect design enables gentle yet secure grasping in unstructured environments. Uniquely, the work investigates the effect of auxetic lattice orientation on grasping conformability, combining experimental validation with 2D Digital Image Correlation (DIC) and nonlinear finite element analysis (FEA). Auxetic configurations with unit cell inclinations of 0 deg, 30 deg, 45 deg, and 60 deg are evaluated, and their grasping forces, deformation responses, and motor torque requirements are systematically compared. Results demonstrate that lattice orientation strongly influences compliance, contact forces, and energy efficiency, with distinct advantages across configurations. This comparative framework highlights the novelty of tailoring auxetic geometries to optimize robotic gripper performance. The findings provide new insights into soft-rigid hybrid gripper design, advancing automation strategies for precision agriculture while minimizing crop damage.

Problem

• Developing hybrid robotic gripper for gentle tomato harvesting
• Analyzing auxetic lattice orientation effects on grasping performance
• Optimizing gripper compliance and energy efficiency in agriculture

Innovation

• Hybrid gripper combines rigid frame with soft auxetic lattice
• Analyzes auxetic lattice orientation effects on grasping performance
• Integrates experimental DIC with nonlinear FEA validation