Acoustic Localization of Underwater Robots: A Time of Arrival-Based Particle Filter Approach Using Asynchronous Beacon Pinging

Underwater robots, despite their wide applications, struggle with localization and navigation in GPS-free environments, a problem potentially solvable by acoustic sensor modules. However, to counteract sensor bias caused by varying factors, the Particle filter algorithm, which employs measurement and motion models for location determination, can be applied and real-time tested for model weight adjustments.In our work, we have developed a Particle Filter Algorithm that takes in the time of arrival of beacon pings as input and uses it to calculate the current position of the robot through a time of arrival particle filter method. We successfully tested the particle filter in a simulated environment by creating an observation model using beacon pings.Our resulting Particle filter algorithm can successfully track a simulated robot with high levels of accuracy within a reasonable run time. In the future, we aim to test the filtering method in real-life scenarios to prove the efficacy of this method in open-water arenas.