Systems and methods for performing inclusive indoor navigation

A system, comprising:

• one or more data storage devices operatively coupled to one or more hardware processors and configured to store instructions configured for execution via the one or more hardware processors to:
• obtain a nested environment data of a facility under consideration for indoor navigation performed by a user, wherein the nested environment data is connected to a server, and wherein the nested environment data of the facility is obtained by:
• creating a two-dimensional digital map for each floor among a plurality of floors of the facility;
• determining a nested map of the facility by sequentially arranging two-dimensional digital maps created for each floor of the facility;
• and
• performing map labelling to localize and capture information of a plurality of landmarks in the nested map;
• receive, by the one or more hardware processors, a destination within the facility from the user;
• estimate, using a surrounding recognition machine learning model, a current spatial location of the user with a predefined precision range at centimeter (cm) level by identifying (i) a user specific area in the facility using the surrounding recognition machine learning model trained with a plurality of real world images of the facility and (ii) the current spatial location of the user with respect to the identified user specific area by triangulating input data received from a plurality of sensors;
• determine an optimal path from the current location to the destination using the nested environment data, wherein the optimal path from the current location to the destination is categorized as at least one of (i) a convenient path (ii) a multi-destination path, and (iii) a shortest path in accordance with one or more user constraints;
• track, using an augmented reality technique, the current spatial location of the user while user navigates on the optimal path from the current location to the destination;
• and
• dynamically update the optimal path from the tracked current spatial location of the user to the destination based on feedback obtained from one or more user interaction modalities.

One or more non-transitory machine readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors causes:

• obtaining a nested environment data of a facility under consideration for indoor navigation performed by a user, wherein the nested environment data is connected to a server, and wherein the nested environment data of the facility is obtained by:
• creating a two-dimensional digital map for each floor among a plurality of floors of the facility;
• determining a nested map of the facility by sequentially arranging two-dimensional digital maps created for each floor of the facility;
• and
• performing map labelling to localize and capture information of a plurality of landmarks in the nested map;
• receiving a destination within the facility from the user;
• estimating using a surrounding recognition machine learning model implemented, a current spatial location of the user with a predefined precision range at centimeter (cm) level by identifying (i) a user specific area in the facility using the surrounding recognition machine learning model trained with a plurality of real world images of the facility and (ii) the current spatial location of the user with respect to the identified user specific area by triangulating input data received from a plurality of sensors;
• determining, an optimal path from the current location to the destination using the nested environment data, wherein the optimal path from the current location to the destination is categorized as at least one of (i) a convenient path (ii) a multi-destination path, and (iii) a shortest path in accordance with one or more user constraints;
• tracking, using an augmented reality technique implemented, the current spatial location of the user while user navigates on the optimal path from the current location to the destination;
• and
• dynamically updating, the optimal path from the tracked current spatial location of the user to the destination based on feedback obtained from one or more user interaction modalities.