Fluidically Innervated Lattices Make Versatile and Durable Tactile Sensors

2025-07-28

AI Summary

To address the need for high-fidelity tactile perception enabling dexterous manipulation and compliant interaction in dynamic, unstructured environments, this paper proposes a passive soft fingertip sensor based on fluidic neuromuscular principles. The sensor is monolithically fabricated via single-material 3D printing of an elastomeric lattice, wherein embedded, sealed microfluidic channels serve directly as pressure-sensing elements—eliminating the need for discrete transducers or heterogeneous materials. This achieves intrinsic structure–sensing integration, high robustness, and scalability. A hybrid approach combining geometric modeling with a lightweight neural network enables real-time, high-accuracy estimation of contact location and full 3D contact forces. Integrated with tactile-feedback-driven admittance control, the system supports stable surface exploration and spring-like compliant responses. Experimental validation confirms no performance degradation under high-frequency impacts and over 10,000 loading cycles, demonstrating substantial improvements in manufacturability, durability, and environmental adaptability.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Humans and AI: Brain-Sensing and Analysis
• Computer Vision: Low Level & Physics-based Vision

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Tactile sensing plays a fundamental role in enabling robots to navigate dynamic and unstructured environments, particularly in applications such as delicate object manipulation, surface exploration, and human-robot interaction. In this paper, we introduce a passive soft robotic fingertip with integrated tactile sensing, fabricated using a 3D-printed elastomer lattice with embedded air channels. This sensorization approach, termed fluidic innervation, transforms the lattice into a tactile sensor by detecting pressure changes within sealed air channels, providing a simple yet robust solution to tactile sensing in robotics. Unlike conventional methods that rely on complex materials or designs, fluidic innervation offers a simple, scalable, single-material fabrication process. We characterize the sensors' response, develop a geometric model to estimate tip displacement, and train a neural network to accurately predict contact location and contact force. Additionally, we integrate the fingertip with an admittance controller to emulate spring-like behavior, demonstrate its capability for environment exploration through tactile feedback, and validate its durability under high impact and cyclic loading conditions. This tactile sensing technique offers advantages in terms of simplicity, adaptability, and durability and opens up new opportunities for versatile robotic manipulation.

Problem

• Developing durable tactile sensors for robots
• Simplifying tactile sensing with fluidic innervation
• Enhancing robotic manipulation and interaction

Innovation

• 3D-printed elastomer lattice with air channels
• Detects pressure changes in sealed channels
• Neural network predicts contact location and force