arXiv:2509.17389cs.RO2025-09

3D打印柔性液态金属传感器,实现对珊瑚等脆弱物体的高精度触觉反馈。

3D Printable Soft Liquid Metal Sensors for Delicate Manipulation Tasks

  • 通过3D扫描自动生成可定制的柔性传感结构,支持复杂自然形态复刻。
  • 能检测低于0.5N的抓握力,精准捕捉珊瑚等脆弱样本的轻触交互。
  • 适用于珊瑚自动化标记与机器人养殖,为脆弱生物操作提供伦理高效方案。

机器人与自动化技术是提升各类受威胁生态系统保护效率的关键。物种普查、数字化建档及饲养等任务需在不损伤脆弱样本的前提下完成交互。基于学习的解决方案还需安全采集数据以训练操控策略,如强化学习。为此,我们提出一种新型方法,可打印自由形态、高度集成的柔性‘物理孪生体’。通过自动化设计流程,从3D扫描或模型出发按需生成复杂可定制的3D软体传感结构。相比现有技术,我们的液态金属软传感器能忠实还原复杂的自然几何形态,并具备优异传感性能,适用于验证精细操作任务的表现。我们以‘感知珊瑚’为例:通过3D打印高保真珊瑚复制品,替代活体实验,提升数据质量,提供伦理且可扩展的自主珊瑚处理路径。桌面及水下抓取实验证明,该感知珊瑚可检测低于0.5N的抓握力,有效捕捉珊瑚处理所需的轻触力。最后,我们在两个场景中展示其价值:(i)自动化珊瑚标签用于实验室识别;(ii)机器人珊瑚养殖。这类感知孪生体比传统传感器提供更丰富的抓握反馈,为部署前验证脆弱物品操作提供实验依据。

原文摘要 · Abstract (English)

Robotics and automation are key enablers to increase throughput in ongoing conservation efforts across various threatened ecosystems. Cataloguing, digitisation, husbandry, and similar activities require the ability to interact with delicate, fragile samples without damaging them. Additionally, learning-based solutions to these tasks require the ability to safely acquire data to train manipulation policies through, 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 manipulation 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 of prior to deployment in handling fragile and delicate items.

3D打印柔性传感机器人抓取生态保护

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