基于离子机器人触觉传感器的类似物体的高效识别
Yongkang Kong1, Guanyin Cheng2, Mengqin Zhang2
1Chongqing Key Laboratory of Generic Technology and System of Service Robots, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Science bulletin
|May 22, 2024
概括
这项研究介绍了一种新的灵活触觉传感器和一个压力滑动双分支卷积神经网络 (PSNet),用于机器人对象识别. 该系统在区分相似物体方面实现了高精度,超越了人类的能力.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 材料科学 材料科学 材料科学
- 人工智能的人工智能
背景情况:
- 机器人触觉感应对于对象识别和交互至关重要.
- 传感器性能和算法的当前局限性阻碍了对类似物体的准确识别.
研究的目的:
- 开发一种高性能灵活的触觉传感器.
- 创建一个智能算法,用于增强触觉识别.
- 提高机器人识别相似物体的能力.
主要方法:
- 一个灵活的传感器的制造,具有金字塔式的微观结构和离子凝涂层.
- 开发一个压力滑动双分支卷积神经网络 (PSNet) 用于特征提取和融合.
- 触觉实验涉及对象识别,特别是在不同类型的叶子上.
主要成果:
- 传感器显示出优异的信号噪声比 (48 dB),低检测极限 (1 Pa),高灵敏度 (92.96 kPa-1),快速响应 (55 ms),以及超过 15,000 个周期的稳定性.
- 公共服务网络实现了97.16%的叶子识别率,超过了人类识别 (72.5%).
结论:
- 开发的灵活触觉传感器和PSNet在机器人触觉传感方面取得了重大进展.
- 这项技术在生物机器人,智能假肢和人机交互方面具有很大的应用潜力.
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