Frontier-Based Exploration Planning for Amphibious Robot with Gaussian Process Occupancy Map

Bo Li, Feng Pan, Shi Zhang, Xiaofei Song, Rongxin Cui

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The autonomous observation of amphibious environments necessitates the robot to possess the capability of simultaneous exploration and mapping. In this article, we present an efficient exploration planning framework for amphibious robot. This method utilizes the Gaussian Process Occupancy Map (GPOM) as a representation of the environment to improve map quality, and Rapidly-exploring Random Trees (RRT) as a global frontier detector for rapid detection of frontiers. Our proposed method has been evaluated through extensive simulations and real-world experiments utilizing a wheel-propeller integrated amphibious robot. The experimental results demonstrate that our approach outperforms other methods in terms of exploration efficiency.

Original languageEnglish
Title of host publication2023 42nd Chinese Control Conference, CCC 2023
PublisherIEEE Computer Society
Pages3889-3894
Number of pages6
ISBN (Electronic)9789887581543
DOIs
StatePublished - 2023
Event42nd Chinese Control Conference, CCC 2023 - Tianjin, China
Duration: 24 Jul 202326 Jul 2023

Publication series

NameChinese Control Conference, CCC
Volume2023-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference42nd Chinese Control Conference, CCC 2023
Country/TerritoryChina
CityTianjin
Period24/07/2326/07/23

Keywords

  • Autonomous Exploration
  • Frontier
  • Gaussian Process Occupancy Map
  • Rapidly-exploring Random Trees
  • Wheel-propeller integrated amphibious robot

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