论文标题
使用触觉指尖的内部对象触及动力学推断
In-Hand Object-Dynamics Inference using Tactile Fingertips
论文作者
论文摘要
具有通过相互作用估算对象属性的能力将使机器人能够操纵新颖的对象。对象的动力学，特别是摩擦和惯性参数，仅在实验室环境中估计具有精确且通常是外部感应的实验室环境。我们能否仅使用机器人的传感器来推断野外物体的动态？在本文中，我们探讨了运动中抓紧物体的动力学的估计，并以多个指尖传感触觉力。我们的估计方法不依赖于扭矩传感来估计动力学。为了估计摩擦，我们开发了一种控制方案，以主动与对象相互作用，直到检测到滑动为止。为了稳健地执行惯性估计，我们设置了一个因子图，该因子图将所有传感器测量值融合在物理一致的流形和执行推理上。我们表明，触觉指尖可以对低质量对象进行手持动态估计。
Having the ability to estimate an object's properties through interaction will enable robots to manipulate novel objects. Object's dynamics, specifically the friction and inertial parameters have only been estimated in a lab environment with precise and often external sensing. Could we infer an object's dynamics in the wild with only the robot's sensors? In this paper, we explore the estimation of dynamics of a grasped object in motion, with tactile force sensing at multiple fingertips. Our estimation approach does not rely on torque sensing to estimate the dynamics. To estimate friction, we develop a control scheme to actively interact with the object until slip is detected. To robustly perform the inertial estimation, we setup a factor graph that fuses all our sensor measurements on physically consistent manifolds and perform inference. We show that tactile fingertips enable in-hand dynamics estimation of low mass objects.
