# Improved Safe Real-time Heuristic Search

## TL;DR

This paper enhances the SafeRTS algorithm for real-time planning by developing an improved framework that guarantees at least equal performance and demonstrates practical effectiveness through experiments.

## Contribution

The paper introduces an improved safe real-time heuristic search framework that builds upon SafeRTS, with theoretical guarantees and empirical validation.

## Key findings

- The new approach performs at least as well as SafeRTS.
- Experimental results confirm the practical effectiveness of the improved framework.
- The framework maintains safety and goal reachability in real-time planning.

## Abstract

A fundamental concern in real-time planning is the presence of dead-ends in the state space, from which no goal is reachable. Recently, the SafeRTS algorithm was proposed for searching in such spaces. SafeRTS exploits a user-provided predicate to identify safe states, from which a goal is likely reachable, and attempts to maintain a backup plan for reaching a safe state at all times. In this paper, we study the SafeRTS approach, identify certain properties of its behavior, and design an improved framework for safe real-time search. We prove that the new approach performs at least as well as SafeRTS and present experimental results showing that its promise is fulfilled in practice.