ε*: An Online Coverage Path Planning Algorithm

被引:57
|
作者
Song, Junnan [1 ]
Gupta, Shalabh [1 ]
机构
[1] Univ Connecticut, Dept Elect & Comp Engn, Storrs, CT 06269 USA
关键词
Adaptive systems; autonomous systems; complete coverage; intelligent robots; path planning; unmanned autonomous vehicles; MOBILE-ROBOT; ENVIRONMENTS; NAVIGATION; AUV;
D O I
10.1109/TRO.2017.2780259
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
This paper presents an algorithm called epsilon*, for online coverage path planning of unknown environment. The algorithm is built upon the concept of an Exploratory Turing Machine (ETM), which acts as a supervisor to the autonomous vehicle to guide it with adaptive navigation commands. The ETM generates a coverage path online using Multiscale Adaptive Potential Surfaces (MAPS), which are hierarchically structured and dynamically updated based on sensor information. The epsilon*-algorithm is computationally efficient, guarantees complete coverage, and does not suffer from the local extrema problem. Its performance is validated by 1) high-fidelity simulations on Player/Stage and 2) actual experiments in a laboratory setting on autonomous vehicles.
引用
收藏
页码:526 / 533
页数:8
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