Bubble Sensor

Bubble sensor research focuses on developing methods for accurately detecting, tracking, and characterizing bubbles in various contexts, from boiling processes to robotic navigation. Current efforts leverage advanced image processing techniques, including deep learning architectures like Mask R-CNN and convolutional neural networks, to analyze bubble size, shape, velocity, and interactions, even in complex, overlapping scenarios. These advancements enable more precise measurements of fluid dynamics, improved tactile sensing in robotics, and more efficient autonomous exploration in challenging environments. The resulting data contributes significantly to fields ranging from materials science and nuclear engineering to robotics and autonomous systems.