Optimizing Source and Sensor Placement for Sound Field Control: An Overview In order to control an acoustic field inside a target region, it is important to choose suitable positions of secondary sources (loudspeakers) and sensors (control pointsmicrophones). This article provides an overview of stateoftheart source and sensor placement methods in sound field control. Although the placement of both sources and sensors greatly affects control accuracy and filter stability, their joint optimization has not been thoroughly investigated in the acoustics literature. In this context, we reformulate five general source andor sensor placement methods that can be applied for sound field control. We compare the performance of these methods through extensive numerical simulations in both narrowband and broadband scenarios.

Towards Soundsource Position Estimation using Mutual Information for Next Best View Motion Planning Robotic operations in the real world rely on bearingonly sensors, e.g., optical, acoustic, etc., to sense physical phenomena. Bearingonly sensors are limited because they do not provide range information. To overcome this limitation in estimating source locations, the most common solutions involve making multiple measurements from different locations, either through multiple sensors in the field or a single moving sensor, and then applying triangulation or filtering. In unknown environments with single motioncapable sensors (e.g., mobile robots with onboard sensors), planned motion of the sensor can allow accurate and efficient source position estimation. This paper presents a novel approach in estimating the locations of stationary sources, using a motioncapable sensor. The proposed method combines the concepts of Extended Kalman Filter (EKF) and Mutual Information (MI) from information theory to estimate the Next Best View (NBV) pose to which the sensor should be moved. A utility function, that accounts for the movement cost, the characteristics of the sensor, and the MI and EKF information, facilitates efficient estimation. The proposed algorithm has been implemented in the realworld for Soundsource Position Estimation (SPE), using an acoustic sensor mounted at the end of a 6 degreesoffreedom (DOF) robotic manipulator. The algorithm, termed as NBVSPE, proves its utility and performance through preliminary indoor and outdoor experiments for sound sources in 3D space.