The auditory system of humanoid robots has gained increased attention in recent years. This system typically acquires the surrounding sound field by means of a microphone array. Signals acquired by the array are then processed using various methods. One of the widely applied methods is direction of arrival estimation. The conventional direction of arrival estimation methods assume that the array is fixed at a given position during the estimation. However, this is not necessarily true for an array installed on a moving humanoid robot. The array motion, if not accounted for appropriately, can introduce a significant error in the estimated direction of arrival. The current paper presents a signal model that takes the motion into account. Based on this model, two processing methods are proposed. The first one compensates for the motion of the robot. The second method is applicable to periodic signals and utilizes the motion in order to enhance the performance to a level beyond that of a stationary array. Numerical simulations and an experimental study are provided, demonstrating that the motion compensation method almost eliminates the motion-related error. It is also demonstrated that by using the motion-based enhancement method it is possible to improve the direction of arrival estimation performance, as compared to that obtained when using a stationary array.

翻译：人形机器人的听觉系统近年来受到越来越多的关注。这类系统通常通过麦克风阵列采集周围声场，并采用多种方法对阵列采集的信号进行处理，其中波达方向估计是广泛应用的方法之一。传统的波达方向估计方法假设阵列在估计过程中固定于某一位置，但对于安装在移动人形机器人上的阵列而言，这一假设不一定成立。若未对阵列运动进行适当处理，可能会在波达方向估计中引入显著误差。本文提出了一种考虑运动影响的信号模型，并基于该模型提出了两种处理方法：第一种方法用于补偿机器人运动带来的影响；第二种方法则针对周期信号，利用运动特性将性能提升至超过固定阵列的水平。数值仿真与实验研究表明，运动补偿方法几乎能完全消除与运动相关的误差，并进一步证明，相较固定阵列，基于运动增强的方法可有效改善波达方向估计性能。