Optimal navigation and object finding without geometric maps or localization

Benjamín Tovar, Steven M. La Valle, Rafael Murrieta

Research output: Contribution to journalConference articlepeer-review


In this paper we develop a dynamic data structure, useful for robot navigation in an unknown, simply-connected planar environment. The guiding philosophy in this work is to avoid traditional problems such as complete map building and localization by constructing a minimal representation based entirely on critical events in online sensor measurements made by the robot. Furthermore, this representation provides a sensor-feedback motion strategy that guides the robot along an optimal trajectory between any two environment locations, and allows the search of static targets, even though there is no geometric map of the environment. We present algorithms for building the data structure in an unknown environment, and for using it to perform optimal navigation. We implemented these algorithms on a real mobile robot. Results are presented in which the robot builds the data structure online, and is able to use it without needing a global reference frame. Simulation results are also shown to demonstrate how the robot is able to find interesting objects in the environment.

Original languageEnglish (US)
Pages (from-to)464-470
Number of pages7
JournalProceedings - IEEE International Conference on Robotics and Automation
StatePublished - 2003
Event2003 IEEE International Conference on Robotics and Automation - Taipei, Taiwan, Province of China
Duration: Sep 14 2003Sep 19 2003

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering


Dive into the research topics of 'Optimal navigation and object finding without geometric maps or localization'. Together they form a unique fingerprint.

Cite this