用微型测距传感器精准识别机械臂附近物体，避免误检自身。
Efficient Detection of Objects Near a Robot Manipulator via Miniature Time-of-Flight Sensors
- 基于机器人自身遮挡的实测模型，实时区分自体与外部物体。
- 可检测靠近臂部的小物体，并定位到机械臂链接上的精确位置。
- 适合需要安全交互的工业场景，尤其适用于空间受限部署。
本文提出一种利用安装在机械臂上的微型飞行时间（Time-of-Flight）传感器，实现对机械臂周围物体的高效检测与定位的方法。使用臂载传感器的关键挑战在于如何区分机器人自身与外部物体的测量信号。为此，我们提出一种计算轻量级方法，利用大量市售低分辨率飞行时间传感器采集的原始数据，建立仅包含机器人自身的预期测量值经验模型，并在运行时据此检测邻近物体。该方法不仅避免了常见配置下的机器人自检问题，还提升了传感器布置的灵活性，实现对机械臂周围更大范围的有效覆盖。实验评估表明，该方法可在不同物体类型、位置及环境光照条件下有效检测小物体，并实现沿机械臂连杆长度的合理定位精度。研究也揭示了测量原理本身带来的性能限制因素。本方法在碰撞规避和人机安全协作中具有潜在应用价值。
原文摘要 · Abstract (English)
We provide a method for detecting and localizing objects near a robot arm using arm-mounted miniature time-of-flight sensors. A key challenge when using arm-mounted sensors is differentiating between the robot itself and external objects in sensor measurements. To address this challenge, we propose a computationally lightweight method which utilizes the raw time-of-flight information captured by many off-the-shelf, low-resolution time-of-flight sensor. We build an empirical model of expected sensor measurements in the presence of the robot alone, and use this model at runtime to detect objects in proximity to the robot. In addition to avoiding robot self-detections in common sensor configurations, the proposed method enables extra flexibility in sensor placement, unlocking configurations which achieve more efficient coverage of a radius around the robot arm. Our method can detect small objects near the arm and localize the position of objects along the length of a robot link to reasonable precision. We evaluate the performance of the method with respect to object type, location, and ambient light level, and identify limiting factors on performance inherent in the measurement principle. The proposed method has potential applications in collision avoidance and in facilitating safe human-robot interaction.
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