This chapter explores mapping, localization, and navigation techniques in robotics, highlighting the role of deep learning in processing high-dimensional sensor data. It discusses various mapping representations - geometric, voxel-based, and semantic - with models like CLIP and NeRF. Additionally, it covers localization methods, diffusion-based navigation strategies like Mobility VLA, and advances in hierarchical learning that improve robot adaptability in complex environments.


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    Title :

    Mapping, Localization, and Navigation


    Contributors:

    Published in:

    AI for Robotics ; Chapter : 6 ; 265-309


    Publication date :

    2025-05-03


    Size :

    45 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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