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Updated: Apr 6, 2026

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
Published on: August 26, 2018
Spatial abstraction for autonomous robot navigation
Susan L Epstein1, Anoop Aroor, Matthew Evanusa
1Department of Computer Science, Hunter College of The City University of New York, New York, NY, USA, susan.epstein@hunter.cuny.edu.
Abstract:
Optimal navigation for a simulated robot relies on a detailed map and explicit path planning, an approach problematic for real-world robots that are subject to noise and error. This paper reports on autonomous robots that rely on local spatial perception, learning, and commonsense rationales instead. Despite realistic actuator error, learned spatial abstractions form a model that supports effective travel.
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