High-Resolution Tactile Fingertip For Intelligent Grasping

Automated dexterous manipulation is critical for enhancing efficiency and precision in aerospace manufacturing and Air Force maintenance operations, where current manual methods are slow, error-prone, and costly. Robotic systems with tactile sensing can significantly improve safety, cost-effectiveness, and readiness. However, existing tactile sensors are too bulky (25–30 mm), lack durability (under 10,000 uses), and have slow data capture rates (25 fps), making them unsuitable for real-world robotic integration. To overcome these challenges, a compact (under 20 mm), high-speed (over 50 fps) tactile sensor will be developed and integrated into multi-fingered robotic hands. First, the tactile sensor will be designed, focusing on optical and material improvements for enhanced durability and sensitivity. The sensors will then be integrated into robotic platforms for dexterous manipulation. Using teleoperation, skilled operators will guide the robots through complex tasks, generating high-quality tactile data. This dataset will be ingested by machine learning models aimed at improving manipulation skills through simulation and real-world feedback. Simulations will model the sensor’s behavior to enable advanced capabilities like slip detection and adaptive force control. The goal is to develop a semi- to fully autonomous robotic system capable of precise, tactile-guided manipulation for logistics, assembly, and inspection tasks.