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首页> 外文会议>The Fourth joint IEEE international conferences on development and learning and epigenetic robotics >Contact force estimation from flexible tactile sensor values considering hysteresis by Gaussian process
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Contact force estimation from flexible tactile sensor values considering hysteresis by Gaussian process

机译：通过高斯过程从考虑滞后的柔性触觉传感器值估算接触力

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摘要

Flexible tactile sensors are important elements for facilitating the physical interaction between robots and uncertain environments. For instance, tactile information is used by the robot to grasp objects and interact with humans. A model-based approach is one technique for building a relationship between tactile sensor values and task-relevant information such as force, slip, and temperature. However, it is difficult to create models of flexible tactile sensors for converting sensor signals beforehand due to a nonlinear relation between a contact and the deformations of the flexible form caused by its hysteresis [1]. In contrast, machine learning techniques can be adopted to represent these relationships. For example, Tada et al. [2] proposed a model to acquire the relationship between tactile sensor values and slip vibration using a neural network.
机译：灵活的触觉传感器是促进机器人与不确定环境之间的物理交互的重要元素。例如，机器人使用触觉信息来抓取物体并与人类互动。基于模型的方法是一种在触觉传感器值和与任务相关的信息（例如力，滑移和温度）之间建立关系的技术。然而，由于接触和由其滞后引起的柔性形式的变形之间的非线性关系，很难预先创建用于转换传感器信号的柔性触觉传感器的模型。相反，可以采用机器学习技术来表示这些关系。例如，Tada等。 [2]提出了一个使用神经网络获取触觉传感器值和滑移振动之间关系的模型。

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