June 30, 2023, 3:48 p.m. | Theo Gervet

Machine Learning Blog | ML@CMU | Carnegie Mellon University blog.ml.cmu.edu

TLDR: Semantic navigation is necessary to deploy mobile robots in uncontrolled environments like our homes, schools, and hospitals. Many learning-based approaches have been proposed in response to the lack of semantic understanding of the classical pipeline for spatial navigation. But learned visual navigation policies have predominantly been evaluated in simulation. How well do different classes of methods work on a robot? We present a large-scale empirical study of semantic visual navigation methods comparing representative methods from classical, modular, and end-to-end …

deploy environments homes hospitals machine learning mobile navigation objects pipeline research robots schools semantic simulation understanding visual navigation world

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Research Scientist, Demography and Survey Science, University Grad

@ Meta | Menlo Park, CA | New York City

Computer Vision Engineer, XR

@ Meta | Burlingame, CA