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Gradient-based Augmentation to Maxima Turn Switching Strategy for Source-Seeking using Sensor-Equipped UAVs
A. Kamthe,
Published in Institute of Electrical and Electronics Engineers Inc.
2020
Pages: 1525 - 1532
Abstract
Localization of an unknown source emanating a radial monotonically varying scalar field in a planar environment by sensor-equipped unmanned aerial vehicles (UAVs) is considered in this paper. The source may be stationary, moving or maneuvering, but of constant signal strength. The only available information is the scalar measurements of the signal field taken by the on-board sensor of the UAV at each time instant. No range or bearing angle information is available to the UAV. Several methodologies have been explored for source seeking in the literature. Among them, a recently proposed algorithm leveraging an inter-loop switched-turn strategy, named 'Maxima Turn Strategy' (MTS), has been found to outperform several other strategies in terms of localization time-efficiency. However, the MTS strategy has a drawback in the sense that between two turn switching points the UAV traverses an entire circular arc, the radius of which corresponds to a pre-fixed nominal turn rate of the UAV. Thus, the MTS could be further improved upon by leveraging information about the gradient estimate updated at the end of the previous loop. Such a gradient-augmented MTS strategy that further reduces the intra-loop traversed path length with quite low memory storage requirement is presented in this paper. Effectiveness of the presented gradient-augmented MTS in terms of source localization time is validated by simulation studies with varied initial geometries for stationary, moving and maneuvering sources. © 2020 IEEE.