A Distributed Algorithmic Approach for Simultaneous Localization and Mapping With Acoustic Sensors

Abstract

The strategies and methods used to implement the problem of acoustic simultaneous localization and mapping (aSLAM) of a differential-drive mobile robot using a concurrent programming approach are described in this paper. The localization problem is confounded by connecting markers to the system’s rear wheels and infrared sensors, allowing improved motion measurement and mapping with piezoelectric ceramic transducers. Two statistical models are given for filtering the outliers in ultrasonic sensor readings. For both localization and mapping, a distributed algorithmic approach is used. The algorithm proposed in this research is implemented on a single-core Arduino UNO board with protothreading for the mobile robot’s linear motion path, and the results are shown. This study indicates that the distributed algorithmic technique reliably conducts aSLAM with noisy low-resolution data implying a low-overhead computational mechanism can perform aSLAM on perceptually sparse data.