We develop service robots using an end-to-end deep learning framework that enables direct learning from perception to action. Our robots, equipped with CNN-powered machine vision, quickly recognize objects and navigate environments, boosting decision accuracy.

Our model optimizes robot behavior strategies through backpropagation training on extensive operational data, including user interactions and machine feedback. This enhances our robots' adaptability and task efficiency, allowing them to operate with increased precision, autonomy, and efficiency.