High Level Path Planning with Uncertainty

TL;DR

This paper introduces U-graph, a novel environment modeling tool that extends distance graphs to incorporate uncertainties, enabling the formulation of optimal navigation plans as Markov decision processes.

Contribution

The paper presents U-graph, a new environment modeling approach that handles uncertainties and provides a general algorithm for optimal navigation planning.

Findings

U-graph effectively models uncertain environments.

A new optimality criterion for navigation plans is defined.

An algorithm for computing optimal navigation plans is proposed.

Abstract

For high level path planning, environments are usually modeled as distance graphs, and path planning problems are reduced to computing the shortest path in distance graphs. One major drawback of this modeling is the inability to model uncertainties, which are often encountered in practice. In this paper, a new tool, called U-yraph, is proposed for environment modeling. A U-graph is an extension of distance graphs with the ability to handle a kind of uncertainty. By modeling an uncertain environment as a U-graph, and a navigation problem as a Markovian decision process, we can precisely define a new optimality criterion for navigation plans, and more importantly, we can come up with a general algorithm for computing optimal plans for navigation tasks.