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A Depth Camera-Based Soft Fingertip Device for Contact Region Estimation and Perception-Action Coupling

机译:基于深度摄像头的软指尖设备,用于接触区域估计和知觉-动作耦合

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As the demand for robotic applications in unconstrained and dynamic environments rises, so does the benefit of advancing the state of the art in soft robotic technologies. However, the complex capabilities of soft robots elicited by their high-dimensional, non-linear characteristics simultaneously yield difficult challenges in control and sensing. Moreover, embedding tactile sensing capabilities in soft materials is often expensive and difficult to fabricate. In recent years, however, the invention of small-scale depth-sensing cameras introduced a promising channel for soft tactile sensor design. In this work, we propose a novel soft device inspired by the human fingertip that not only utilizes a small depth camera as the perception mechanism, but also possesses compliance-modulating capabilities. We demonstrate its ability to accurately estimate contact regions upon interaction with an external obstacle, and show that the estimation sensitivity can be modulated via internal fluid states. In addition, we determine an empirical model of the device's force-deformation characteristics under simplifying assumptions, and validate its performance with real-time force matching control experiments.
机译:随着在不受约束的动态环境中对机器人应用程序的需求不断增加,推进软机器人技术的发展水平的好处也在增加。但是,软机器人的高维,非线性特性引起的复杂功能同时给控制和传感带来了艰巨的挑战。而且,将触觉感测能力嵌入软材料中通常是昂贵的并且难以制造。但是,近年来,小型深度感应相机的发明为软触觉传感器设计引入了一个有希望的渠道。在这项工作中,我们提出了一种受人的指尖启发的新型软设备,该软设备不仅利用小深度相机作为感知机制,而且还具有顺应性调节功能。我们证明了它具有在与外部障碍物相互作用时准确估计接触区域的能力,并表明可以通过内部流体状态来调节估计灵敏度。此外,我们在简化的假设下确定了设备力变形特性的经验模型,并通过实时力匹配控制实验验证了其性能。

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