AUTONOMOUS ROBOT WITH DEEP LEARNING ENVIRONMENT RECOGNITION AND SENSOR CALIBRATION

The technology disclosed includes systems and methods for a mobile platform such as a robot system that includes one or more deep learning models to avoid objects in an environment. The method includes using a deep learning trained classifier, deployed in a robot system, to detect obstacles and avoid obstructions in an environment in which a robot moves based upon image information. The image information is captured by at least one visual spectrum-capable camera that captures images in a visual spectrum (RGB) range and at least one depth measuring camera. An identity for objects is determined corresponding to the features as extracted from the images. The method includes determining an occupancy map of the environment using the ensemble of trained neural network classifiers. The occupancy map is provided to a process for initiating robot movement to avoid objects in the occupancy map of the environment.