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ε*: An Online Coverage Path Planning Algorithm
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DOI：10.1109/TRO.2017.2780259.png)
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Abstract
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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.
Keywords:
Adaptive systems
autonomous systems
complete coverage
intelligent robots
path planning
unmanned autonomous vehicles
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