Towards the goal of robots performing robust and intelligent physical interactions with people, it is crucial that robots are able to accurately sense the human body, follow trajectories around the body, and track human motion. This study introduces a capacitive servoing control scheme that allows a robot to sense and navigate around human limbs during close physical interactions. Capacitive servoing leverages temporal measurements from a multi-electrode capacitive sensor array mounted on a robot's end effector to estimate the relative position and orientation (pose) of a nearby human limb. Capacitive servoing then uses these human pose estimates from a data-driven pose estimator within a feedback control loop in order to maneuver the robot's end effector around the surface of a human limb. We provide a design overview of capacitive sensors for human-robot interaction and then investigate the performance and generalization of capacitive servoing through an experiment with 12 human participants. The results indicate that multidimensional capacitive servoing enables a robot's end effector to move proximally or distally along human limbs while adapting to human pose. Using a cross-validation experiment, results further show that capacitive servoing generalizes well across people with different body size.
翻译:实现机器人与人进行强健和智能物理互动的目标, 机器人能够准确感知人体身体, 跟踪身体周围的轨迹, 跟踪人体运动, 至关重要。 本研究引入了一种电动静脉冲控制方案, 允许机器人在近距离物理互动期间在人体肢体周围感知和导航。 电动静脉冲通过机器人终端效果器上安装的多电子电动感应阵列进行时间测量, 以估计附近人体肢体的相对位置和方向( 位置 ) 。 电动静脉冲后, 在反馈控制循环中使用数据驱动的人体姿势估计仪, 以在人体肢体表面操作机器人的内脏效应。 我们提供人类机器人相互作用的电动感应器的设计概览, 然后通过对12名人类参与者的实验来调查电动感应感应传感器的性能和总体性能。 结果显示, 机器人的多功能感应力跳动力使机器人的尾部能能能在数据驱动性或偏振动性天体上移动, 使普通肢体的机体进行不同的实验。