Abstract
Perception using whisker-inspired tactile sensors currently faces a major challenge: the lack of active control in robots based on direct contact information from the whisker. To accurately reconstruct object contours, it is crucial for the whisker sensor to continuously follow and maintain an appropriate relative touch pose on the surface. This is especially important for localization based on tip contact, which has a low tolerance for sharp surfaces and must avoid slipping into tangential contact. In this paper, we first construct a magnetically transduced whisker sensor featuring a compact and robust suspension system composed of three flexible spiral arms. We develop a method that leverages a characterized whisker deflection profile to directly extract the tip contact position using gradient descent, with a Bayesian filter applied to reduce fluctuations. We then propose an active motion control policy to maintain the optimal relative pose of the whisker sensor against the object surface. A B-Spline curve is employed to predict the local surface curvature and determine the sensor orientation. Results demonstrate that our algorithm can effectively track objects and reconstruct contours with sub-millimeter accuracy. Finally, we validate the method in simulations and real-world experiments where a robot arm drives the whisker sensor to follow the surfaces of three different objects.
Abstract (translated)
当前，基于触须灵感的触觉传感器在感知领域面临的主要挑战是机器人缺乏对直接接触信息进行主动控制的能力。为了精确地重建物体轮廓，触须传感器需要持续跟踪并保持适当的相对接触姿态。这尤其对于依赖于尖端接触定位的方法来说至关重要，因为这类方法对于锋利表面具有较低的容忍度，并且必须避免进入切向接触状态。 在本文中，我们首先构建了一种磁感应式触须传感器，该传感器配备了由三个灵活螺旋臂组成的紧凑而坚固的悬挂系统。接下来，开发了一种利用已知触须偏转特征直接通过梯度下降法提取尖端接触位置的方法，并应用贝叶斯滤波来减少波动。此外，我们还提出了一种主动运动控制策略，以保持触须传感器相对于物体表面的最佳相对姿态。 为了预测局部曲率并确定传感器的方向，使用了B样条曲线。实验结果表明，我们的算法能够有效地跟踪对象并实现次毫米精度的轮廓重建。最后，在模拟和真实世界的试验中验证了该方法的有效性——在这些试验中，机器人手臂驱动触须传感器沿三个不同物体表面进行接触跟踪。 总的来说，这项研究为利用机械式触觉传感器执行复杂的定位任务提供了一种新的途径，并有助于改善基于直接接触的感知系统。
URL
https://arxiv.org/abs/2507.23305
