Miguel Flores-Acton | Searcharxiv

arXiv2026

Printed helicoids with embedded air channels make sensorized segments for soft continuum robots

Soft robots enable safe, adaptive interaction with complex environments but remain difficult to sense and control due to their highly deformable structures. Architected soft materials such as helicoid lattices offer tunable stiffness and strength but are challenging to instrument because of their sparse geometry. We introduce a fabrication method for embedding air channels into helicoid-based soft continuum robots. Multi-material segments fabricated via vision-controlled jetting in a single print interface with PCBs housing miniature pressure sensors and IMUs for distributed deformation sensing. We characterize the mechanical properties of four helicoid designs and validate the sensor response to fundamental deformation modes. To demonstrate the platform's scalability, we construct and mechanically evaluate a meter-scale, 14-DoF cable-driven soft arm capable of open-loop trajectory tracking and object grasping, with tactile-based stiffness detection demonstrated using the gripper sensors. This approach establishes a scalable fabrication strategy for sensorized architected materials in large-scale soft robotic systems.

cs.RO↗

arXiv2025

Fluidically Innervated Lattices Make Versatile and Durable Tactile Sensors

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.

cs.RO↗