3D Printable Soft Liquid Metal Sensors for Delicate Manipulation Tasks
Lois Liow, Jonty Milford, Emre Uygun, Andre Farinha, VinothKumar Viswanathan, Joshua Pinskier, David Howard
AI summary
Problem
Robotic handling of fragile, complex specimens like corals risks damage and lacks safe, high-fidelity environments for training and validation. Existing sensors fail to capture nuanced, low-force interactions across irregular geometries.
Approach
An automated workflow generates continuous hollow channels within 3D object scans, which are monolithically 3D printed and filled with liquid metal to create soft, sensorized replicas that faithfully mimic delicate physical interactions.
Key results
- Automated channel generation pipeline for arbitrary 3D geometries
- Support-free SLA 3D printing of watertight soft sensors
- Sub-0.5 N force detection with high sensitivity and cycle stability
- Validated performance in automated coral labeling and underwater grasping
Why it matters
Provides an ethical, scalable, and high-fidelity testing platform for training and validating robotic manipulation systems before deployment on fragile real-world specimens.
Abstract
Robotics and automation are key enablers to increase throughput in ongoing conservation efforts across various threatened ecosystems. Cataloguing, digitisation, hus- bandry, and similar activities require the ability to interact with delicate, fragile samples without damaging them. Addi- tionally, learning-based solutions to these tasks require the ability to safely acquire data to train manipulation policies, e.g., reinforcement learning. To address these twin needs, we introduce a novel method to print free-form, highly sensorised soft ‘physical twins’. We present an automated design workflow to create complex and customisable 3D soft sensing structures on demand from 3D scans or models. Compared to the state of the art, our soft liquid metal sensors faithfully recreate complex natural geometries and display excellent sensing properties suitable for validating performance in delicate manipulation tasks. We demonstrate the application of our physical twins as ’sensing corals’: high-fidelity, 3D printed replicas of scanned corals that eliminate the need for live coral experimentation, whilst increasing data quality, offering an ethical and scalable pathway for advancing autonomous coral handling and soft manipulation broadly. Through extensive bench-top manipula- tion and underwater grasping experiments, we show that our sensing coral is able to detect grasps under 0.5 N, effectively capturing the delicate interactions and light contact forces required for coral handling. Finally, we showcase the value of our physical twins across two demonstrations: (i) automated coral labelling for lab identification and (ii) robotic coral aquaculture. Sensing physical twins such as ours can provide richer grasping feedback than conventional sensors providing experimental validation prior to deployment in handling fragile and delicate items.