  For underwater vehicles, robotic applications have the added difficulty of
operating in highly unstructured and dynamic environments. Environmental
effects impact not only the dynamics and controls of the robot but also the
perception and sensing modalities. Acoustic sensors, which inherently use
mechanically vibrated signals for measuring range or velocity, are particularly
prone to the effects that such dynamic environments induce. This paper presents
an uncertainty-aware localization and mapping framework that accounts for
induced disturbances in acoustic sensing modalities for underwater robots
operating near the surface in dynamic wave conditions. For the state estimation
task, the uncertainty is accounted for as the added noise caused by the
environmental disturbance. The mapping method uses an adaptive kernel-based
method to propagate measurement and pose uncertainty into an occupancy map.
Experiments are carried out in a wave tank environment to perform qualitative
and quantitative evaluations of the proposed method. More details about this
project can be found at https://umfieldrobotics.github.io/PUMA.github.io.
