仿蟑螂触角的微型触觉传感器，让微小机器人也能精准感知环境。
Design of a bioinspired robophysical antenna for insect-scale tactile perception and navigation
- 仿生分段柔性结构，内置电容角度传感器，被动弯曲响应环境刺激。
- 静态/动态弯曲误差仅0.79°和3.58°，可精准测量距离、间隙与表面纹理。
- 体积小、重量轻、功耗低，适合微型机器人自主导航与避障。
美洲蟑螂（Periplaneta americana）利用其柔软触角通过数万个分布式机械感受器提取丰富的触觉信息以指导决策。尽管触觉传感器能在自然系统中实现鲁棒、自主的感知与导航，但受限于尺寸、重量和功耗，现有技术难以在昆虫尺度机器人上复现此类能力。为此，我们提出CITRAS（Cockroach Inspired Tactile Robotic Antenna Sensor），一种仿生、多段式、柔性的层压触觉传感器，内置电容式角度传感器。该传感器尺寸为73.7×15.6×2.1 mm，重491 mg，功耗仅32 mW，可无缝集成于微型机器人平台。其分段柔性结构能被动弯曲，静态弯曲最大误差0.79°，动态弯曲最大误差3.58°。实验表明，该传感器可实现基底到尖端距离预测误差7.75%，环境间隙宽度估计误差6.73%，并通过差异响应区分表面纹理。未来将此仿生触觉天线集成于昆虫尺度机器人，有望填补关键感知空白，提升复杂狭窄环境中的自主探索、避障与环境建图能力。
原文摘要 · Abstract (English)
The American cockroach (Periplaneta americana) uses its soft antennae to guide decision making by extracting rich tactile information from tens of thousands of distributed mechanosensors. Although tactile sensors enable robust, autonomous perception and navigation in natural systems, replicating these capabilities in insect-scale robots remains challenging due to stringent size, weight, and power constraints that limit existing sensor technologies. To overcome these limitations, we introduce CITRAS (Cockroach Inspired Tactile Robotic Antenna Sensor), a bioinspired, multi-segmented, compliant laminate sensor with embedded capacitive angle sensors. CITRAS is compact (73.7x15.6x2.1 mm), lightweight (491 mg), and low-power (32 mW), enabling seamless integration with miniature robotic platforms. The segmented compliant structure passively bends in response to environmental stimuli, achieving accurate hinge angle measurements with maximum errors of just 0.79 degree (quasistatic bending) and 3.58 degree (dynamic bending). Experimental evaluations demonstrate CITRAS' multifunctional tactile perception capabilities: predicting base-to-tip distances with 7.75 % error, estimating environmental gap widths with 6.73 % error, and distinguishing surface textures through differential sensor response. The future integration of this bioinspired tactile antenna in insect-scale robots addresses critical sensing gaps, promising enhanced autonomous exploration, obstacle avoidance, and environmental mapping in complex, confined environments.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。