Deliberate Exploration Supports Navigation in Unfamiliar Worlds

TL;DR

This paper presents a robot navigation system that combines deliberate exploration with planning in a cognitive spatial model, enabling efficient navigation in unfamiliar indoor environments despite limited exploration.

Contribution

It introduces a novel approach that integrates deliberate exploration with planning based on spatial affordances for improved navigation in new environments.

Findings

Faster planning in the cognitive spatial model.

Successful navigation despite limited exploration.

Enhanced understanding of environment connectivity.

Abstract

To perform tasks well in a new domain, one must first know something about it. This paper reports on a robot controller for navigation through unfamiliar indoor worlds. Based on spatial affordances, it integrates planning with reactive heuristics. Before it addresses specific targets, however, the system deliberately explores for high-level connectivity and captures that data in a cognitive spatial model. Despite limited exploration time, planning in the resultant model is faster and better supports successful travel in a challenging, realistic space.