Information technology asset type identification using a mobile vision-enabled robot

A computer program product comprising a non-transitory computer readable medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to:

• receive a digital image of an obstacle from an image capture device of an automated robot;
• perform a classification operation on the digital image of the obstacle to identify a proposed asset type classification for the obstacle;
• determine a final asset type for the obstacle based on the proposed asset type classification for the obstacle;
• and
• update a map data structure for a physical premises in which the obstacle is present based on the final asset type, wherein the computer readable program further causes the computing device to perform the classification operation at least by:
• gathering additional sensor information from one or more other sensors provided on either the robot or in the physical premises;
• and
• performing the classification operation based on a classification of characteristics of the obstacle obtained from analysis of the digital image and analysis of the additional sensor information, wherein the additional sensor information comprises information indicative of environmental conditions within a vicinity of the obstacle, that together with the digital image of the obstacle, are indicative of an asset type classification of the obstacle.

An apparatus comprising:

• a processor;
• and
• a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to:
• receive a digital image of an obstacle from an image capture device of an automated robot;
• perform a classification operation on the digital image of the obstacle to identify a proposed asset type classification for the obstacle;
• determine a final asset type for the obstacle based on the proposed asset type classification for the obstacle;
• and
• update a map data structure for a physical premises in which the obstacle is present based on the final asset type, wherein the instructions further cause the processor to perform the classification operation at least by:
• gathering additional sensor information from one or more other sensors provided on either the robot or in the physical premises;
• and
• performing the classification operation based on a classification of characteristics of the obstacle obtained from analysis of the digital image and analysis of the additional sensor information, wherein the additional sensor information comprises information indicative of environmental conditions within a vicinity of the obstacle, that together with the digital image of the obstacle, are indicative of an asset type classification of the obstacle.