Synergistic exploration and navigation of mobile robots under pose uncertainty in unknown environments

Ioannis Arvanitakis, Anthony Tzes, Konstantinos Giannousakis

Research output: Contribution to journalArticle

1 Citation (Scopus)
32 Downloads (Pure)

Abstract

Path planning under uncertainty in an unknown environment is an arduous task as the resulting map has inaccuracies and a safe path cannot always be found. A path planning method is proposed in unknown environments towards a known target position and under pose uncertainty. A limited range and limited field of view range sensor is considered and the robot pose can be inferred within certain bounds. Based on the sensor measurements a modified map is created to be used for the exploration and path planning processes, taking into account the uncertainty via the calculation of the guaranteed visibility and guaranteed sensed area, where safe navigation can be ensured regardless of the pose-error. A switching navigation function is used to initially explore the space towards the target position, and afterwards, when the target is discovered to navigate the robot towards it. Simulation results highlighting the efficiency of the proposed scheme are presented.

Original languageEnglish
Pages (from-to)(in press)
Number of pages10
JournalInternational Journal of Advanced Robotic Systems
Volume15
Issue number1
DOIs
Publication statusPublished - 1 Jan 2018

Bibliographical note

This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage)

Keywords

  • Autonomous robotic systems
  • Exploration
  • Guidance navigation and control
  • Mobile robots
  • Motion planning

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Artificial Intelligence

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