Temporal-Logic-Aware Frontier-Based Exploration

TL;DR

This paper presents a novel frontier-based exploration algorithm that incorporates temporal logic and commit states to enable autonomous robots to satisfy complex temporal specifications in unknown environments.

Contribution

It introduces commit states for capturing irreversible task progress and develops a sound, complete exploration method that ensures task satisfaction possibilities are preserved.

Findings

Validated through simulations demonstrating effectiveness.

Ensures all possible satisfaction paths are preserved.

Guides robots efficiently towards satisfying temporal logic specifications.

Abstract

This paper addresses the problem of temporal logic motion planning for an autonomous robot operating in an unknown environment. The objective is to enable the robot to satisfy a syntactically co-safe Linear Temporal Logic (scLTL) specification when the exact locations of the desired labels are not known a priori. We introduce a new type of automaton state, referred to as commit states. These states capture intermediate task progress resulting from actions whose consequences are irreversible. In other words, certain future paths to satisfaction become not feasible after taking those actions that lead to the commit states. By leveraging commit states, we propose a sound and complete frontier-based exploration algorithm that strategically guides the robot to make progress toward the task while preserving all possible ways of satisfying it. The efficacy of the proposed method is validated through simulations.