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通过触摸穿越:基于触摸的机器人穿越,在复杂的环境中使用人工皮肤

Adam Mazurick¹, Alex Ferworn¹

¹Department of Computer Science, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada.

Sensors (Basel, Switzerland)

|November 13, 2025

概括

使用存储器增强策略 (M3) 的触摸优先机器人穿越显示了所有照明条件的稳定性,包括黑暗. 这种方法提供了光线独立的导航,对于具有挑战性的环境至关重要.

科学领域:

机器人技术机器人技术机器人技术
人工智能的人工智能
传感器融合式传感器

背景情况:

机器人导航通常依赖于视觉传感器,这些传感器容易受到不同的照明条件的影响.
为可见度差 (黑暗,烟雾) 的环境开发强大的导航系统是一个重大挑战.
触觉传感为机器人移动提供了一个潜在的替代或补充模式.

研究的目的:

为了评估DHS图-8移动性测试上的触觉第一机器人穿越算法的性能.
在不同的照明条件下,将不同触觉策略的稳定性与基于视觉和触觉的直方图基线进行比较.
通过触摸感应来评估光线独立导航的可行性.

主要方法:

使用双向重复测量设计,测试多个算法 (M1,M2,M3,CB-V,T-VFH,T-D* Lite) 在室内,室外和黑暗的照明条件下.
为测试使用了定制的Eleven机器人,这是一只四足动物,配有关节装配的触觉传感器 (FSR,CNT线).
使用ESP32-S3,Arduino Nano 33 BLE,Raspberry Pi 400和迷你VESC控制器实现了无线控制和传感.

主要成果:

触摸堆在所有照明条件下,包括完全黑暗中,实现了大约21毫秒的政策延迟 (p50) 和80%的成功率.
与相机基线 (CB-V) 相比,记忆增强触摸策略 (M3) 显示出一致的稳定性,室内性能降低仅为3-4%,室外/黑暗时降低13-16%.
没有证实M3和CB-V之间的速度等价,这表明速度和稳健性之间的权衡.

结论:

触摸-首先穿越,特别是在内存增强的政策,提供照明独立的导航功能.
这种方法对于机器人在具有挑战性照明或纹理条件的环境中工作至关重要.
该研究强调了触觉感应对强大可靠机器人导航的潜力,将适度的速度与增强的感应独立性进行交易.

关键词:

人造皮肤的人造皮肤.图8 DHS 的基准指标照明的强度灯光的强度增强记忆的政策政策机器人穿越穿越的过程触觉感应是一种触觉感应.

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