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Gap navigation trees: Minimal representation for visibility-based tasks (2004)
| Venue: | In Proc. Workshop on the Algorithmic Foundations of Robotics |
| Citations: | 30 - 9 self |
BibTeX
@INPROCEEDINGS{Tovar04gapnavigation,
author = {Benjamín Tovar and Luis Guilamo and Steven M. Lavalle},
title = {Gap navigation trees: Minimal representation for visibility-based tasks},
booktitle = {In Proc. Workshop on the Algorithmic Foundations of Robotics},
year = {2004},
pages = {11--26}
}
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Abstract
Abstract. In this paper we present our advances in a data structure, the Gap Navigation Tree (GNT), useful for solving different visibility-based robotic tasks in unknown planar environments. We present its use for optimal robot navigation in simply-connected environments, locally optimal navigation in multiply-connected environments, pursuit-evasion, and robot localization. The guiding philosophy of this work is to avoid traditional problems such as complete map building and exact localization by constructing a minimal representation based entirely on critical events in online sensor measurements made by the robot. The data structure is introduced from an information space perspective, in which the information used among the different visibility-based tasks is essentially the same, and it is up to the robot strategy to use it accordingly for the completion of the particular task. This is done through a simple sensor abstraction that reports the discontinuities in depth information of the environment from the robot’s perspective (gaps), and without any kind of geometric measurements. The GNT framework was successfully implemented on a real robot platform. 1
Keyphrases
gap navigation tree minimal representation visibility-based task data structure simple sensor abstraction gnt framework online sensor measurement real robot platform robot strategy exact localization multiply-connected environment particular task information space perspective robot localization critical event optimal robot navigation traditional problem robot perspective unknown planar environment complete map building different visibility-based robotic task simply-connected environment depth information geometric measurement different visibility-based task optimal navigation
