Generating and/or using training instances that include previously captured robot vision data and drivability labels

A robot, comprising:

• one or more processors, and
• memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations that include:
• generating first vision data using one or more first vision components that are in communication with the one or more processors,
• wherein the first vision data characterizes a portion of an area that is within a viewable region of the one or more first vision components;
• determining, based on the first vision data, whether the portion of the area includes a surface that is traversable;
• generating second vision data that characterizes a separate portion of the area,
• wherein the second vision data is generated using one or more second vision components that are:
• separate from the one or more first vision components, and also in communication with the one or more processors;
• determining, based on the second vision data, whether an additional surface included in the separate portion of the area is traversable,
• wherein determining whether the additional surface that is traversable is performed using one or more machine learning models, and
• wherein the one or more machine learning models are trained using one or more instances of training data that characterize drivability of one or more particular surfaces;
• and
• operating according to whether the surface and the additional surface are determined to be traversable.