Abstract: Systems, apparatuses, and methods for rapid machine learning for floor segmentation for robotic devices are disclosed herein. According to at least one non-limiting exemplary embodiment, a robotic system is disclosed. The robotic system may comprise a neural network embodied therein capable of learning associations between color values of pixels and corresponding classifications of those pixels, wherein neural network is trained initially to identify floor and non-floor pixels within images. A user input may be provided to the neural network to further configure the neural network to be able to identify navigable floors and unnavigable floors unique to an environment without a need for additional annotated training images specific to the environment.

Abstract: Systems, apparatuses, and methods for rapid machine learning for floor segmentation for robotic devices are disclosed herein. According to at least one non-limiting exemplary embodiment, a robotic system is disclosed. The robotic system may comprise a neural network embodied therein capable of learning associations between color values of pixels and corresponding classifications of those pixels, wherein neural network is trained initially to identify floor and non-floor pixels within images. A user input may be provided to the neural network to further configure the neural network to be able to identify navigable floors and unnavigable floors unique to an environment without a need for additional annotated training images specific to the environment.