Multi-Objective Path-Based D* Lite - Robotics Institute Carnegie Mellon University

Multi-Objective Path-Based D* Lite

Zhongqiang Ren, Sivakumar Rathinam, Maxim Likhachev, and Howie Choset
Journal Article, IEEE Robotics and Automation Letters, 2022

Abstract

Incremental graph search algorithms such as D* Lite reuse previous, and perhaps partial, searches to expedite subsequent path planning tasks. In this article, we are interested in developing incremental graph search algorithms for path finding problems to simultaneously optimize multiple objectives such as travel risk, arrival time, etc. This is challenging because in a multi-objective setting, the number of ‘`Pareto-optimal’' solutions can grow exponentially with respect to the size of the graph. This article presents a new multi-objective incremental search algorithm called Multi-Objective Path-Based D* Lite (MOPBD*) which leverages a path-based expansion strategy to prune dominated solutions. Additionally, we introduce two variants of MOPBD* to further improve search efficiency and to approximate the Pareto-optimal front. We numerically evaluate the performance of MOPBD* and its variants in various maps with two and three objectives. Results show that our approach is more efficient than search from scratch, and runs up to an order of magnitude faster than the existing incremental method for multi-objective path planning.

BibTeX

@article{Ren-2022-130813,
author = {Zhongqiang Ren and Sivakumar Rathinam and Maxim Likhachev and Howie Choset},
title = {Multi-Objective Path-Based D* Lite},
journal = {IEEE Robotics and Automation Letters},
year = {2022},
month = {January},
}