Learning to Navigate from Scratch using World Models and Curiosity: the Good, the Bad, and the Ugly

TL;DR

This paper introduces a navigation system combining world models with curiosity-driven exploration, demonstrating rapid environment coverage in simulations but facing challenges in larger, dynamic real-world settings.

Contribution

It presents an integrated approach for autonomous navigation that leverages curiosity and world models, highlighting the importance of adaptability in complex environments.

Findings

Rapid exploration in simulated environments

Challenges in scaling to larger, dynamic real-world environments

Need for more adaptable world models

Abstract

Learning to navigate unknown environments from scratch is a challenging problem. This work presents a system that integrates world models with curiosity-driven exploration for autonomous navigation in new environments. We evaluate performance through simulations and real-world experiments of varying scales and complexities. In simulated environments, the approach rapidly and comprehensively explores the surroundings. Real-world scenarios introduce additional challenges. Despite demonstrating promise in a small controlled environment, we acknowledge that larger and dynamic environments can pose challenges for the current system. Our analysis emphasizes the significance of developing adaptable and robust world models that can handle environmental changes to prevent repetitive exploration of the same areas.