智能轮胎融合视觉与触觉数据，实现高精度地形识别与损伤检测。
VTire: A Bimodal Visuotactile Tire with High-Resolution Sensing Capability
- 采用双模态传感设计，同步采集视觉与触觉信息。
- 地形分类准确率达99.2%，损伤检测准确率97%。
- 适合机器人、自动驾驶车辆的环境感知研究者使用。
开发具备高感知能力的智能轮胎对提升轮式机器人和车辆的移动稳定性与环境适应性至关重要。然而，传统制造工艺使轮胎难以精确推断外部信息。为此，本文提出一种双模态触觉-视觉智能轮胎，可同步获取触觉与视觉数据。借助新兴的多模态感知技术，该轮胎实现了地形识别、地面裂缝检测、载荷感知及胎体损伤检测等多种功能。同时，优化了轮胎材料与结构，使其具备优异的弹性、韧性、硬度与透明性。算法方面，开发了基于Transformer的多模态分类算法、基于有限元分析的载荷检测方法以及接触分割算法。此外，构建智能移动平台验证系统有效性，并在复杂地形中建立视觉与触觉数据集。实验结果表明，多模态地形感知算法分类准确率达99.2%，损伤检测准确率为97%，物体搜索成功率达98%，可承受超过35 kg的载重。相关算法、硬件与数据集已开源：https://sites.google.com/view/vtire。
原文摘要 · Abstract (English)
Developing smart tires with high sensing capability is significant for improving the moving stability and environmental adaptability of wheeled robots and vehicles. However, due to the classical manufacturing design, it is always challenging for tires to infer external information precisely. To this end, this paper introduces a bimodal sensing tire, which can simultaneously capture tactile and visual data. By leveraging the emerging visuotactile techniques, the proposed smart tire can realize various functions, including terrain recognition, ground crack detection, load sensing, and tire damage detection. Besides, we optimize the material and structure of the tire to ensure its outstanding elasticity, toughness, hardness, and transparency. In terms of algorithms, a transformer-based multimodal classification algorithm, a load detection method based on finite element analysis, and a contact segmentation algorithm have been developed. Furthermore, we construct an intelligent mobile platform to validate the system's effectiveness and develop visual and tactile datasets in complex terrains. The experimental results show that our multimodal terrain sensing algorithm can achieve a classification accuracy of 99.2\%, a tire damage detection accuracy of 97\%, a 98\% success rate in object search, and the ability to withstand tire loading weights exceeding 35 kg. In addition, we open-source our algorithms, hardware, and datasets at https://sites.google.com/view/vtire.
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