Multiple UAV Adaptive Navigation for Three-Dimensional Scalar Fields
Adaptive Navigation (AN) control strategies allow an agent to autonomously alter its trajectory based on realtime measurements of the environment. Compared to conventional navigation methods, these techniques can reduce required time and energy to explore scalar characteristics of unknown and dynami...
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doaj-ba4fae49df3d49e88ff27b1a61f8fa592021-09-15T23:00:13ZengIEEEIEEE Access2169-35362021-01-01912262612265410.1109/ACCESS.2021.31078549522136Multiple UAV Adaptive Navigation for Three-Dimensional Scalar FieldsRobert K. Lee0https://orcid.org/0000-0003-3515-0298Christopher A. Kitts1https://orcid.org/0000-0001-8078-9360Michael A. Neumann2https://orcid.org/0000-0001-7419-6534Robert T. Mcdonald3https://orcid.org/0000-0001-9781-8260Department of Mechanical Engineering, Santa Clara University, Santa Clara, CA, USADepartment of Mechanical Engineering, Santa Clara University, Santa Clara, CA, USADepartment of Mechanical Engineering, Santa Clara University, Santa Clara, CA, USADepartment of Mechanical Engineering, Santa Clara University, Santa Clara, CA, USAAdaptive Navigation (AN) control strategies allow an agent to autonomously alter its trajectory based on realtime measurements of the environment. Compared to conventional navigation methods, these techniques can reduce required time and energy to explore scalar characteristics of unknown and dynamic regions of interest (e.g., temperature, concentration level). Multiple Uncrewed Aerial Vehicle (UAV) approaches to AN can improve performance by exploiting synchronized spatially-dispersed measurements to generate realtime information regarding the structure of the local scalar field, which is then used to inform navigation decisions. This article presents initial results of a comprehensive program to develop, verify, and experimentally implement mission-level AN capabilities in three-dimensional (3D) space using our unique multilayer control architecture for groups of vehicles. Using our flexible formation control system, we build upon our prior 2D AN work and provide new contributions to 3D scalar field AN by a) demonstrating a wide range of 3D AN capabilities using a unified, multilayer control architecture, b) extending multivehicle 2D AN control primitives to navigation in 3D scalar fields, and c) introducing state-based sequencing of these primitive AN functions to execute 3D mission-level capabilities such as isosurface mapping and plume following. We verify functionality using high-fidelity simulations of multicopter drone clusters, accounting for vehicle dynamics, outdoor wind gust disturbances, position sensor inaccuracy, and scalar field sensor noise. This paper presents the multilayer architecture for multivehicle formation control, the 3D AN control primitives, the sequencing approaches for specific mission-level capabilities, and simulation results that demonstrate these functions.https://ieeexplore.ieee.org/document/9522136/Adaptive navigationautonomous navigationcluster-space controlcontour mappingcooperative controlextrema seeking |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Robert K. Lee Christopher A. Kitts Michael A. Neumann Robert T. Mcdonald |
spellingShingle |
Robert K. Lee Christopher A. Kitts Michael A. Neumann Robert T. Mcdonald Multiple UAV Adaptive Navigation for Three-Dimensional Scalar Fields IEEE Access Adaptive navigation autonomous navigation cluster-space control contour mapping cooperative control extrema seeking |
author_facet |
Robert K. Lee Christopher A. Kitts Michael A. Neumann Robert T. Mcdonald |
author_sort |
Robert K. Lee |
title |
Multiple UAV Adaptive Navigation for Three-Dimensional Scalar Fields |
title_short |
Multiple UAV Adaptive Navigation for Three-Dimensional Scalar Fields |
title_full |
Multiple UAV Adaptive Navigation for Three-Dimensional Scalar Fields |
title_fullStr |
Multiple UAV Adaptive Navigation for Three-Dimensional Scalar Fields |
title_full_unstemmed |
Multiple UAV Adaptive Navigation for Three-Dimensional Scalar Fields |
title_sort |
multiple uav adaptive navigation for three-dimensional scalar fields |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
Adaptive Navigation (AN) control strategies allow an agent to autonomously alter its trajectory based on realtime measurements of the environment. Compared to conventional navigation methods, these techniques can reduce required time and energy to explore scalar characteristics of unknown and dynamic regions of interest (e.g., temperature, concentration level). Multiple Uncrewed Aerial Vehicle (UAV) approaches to AN can improve performance by exploiting synchronized spatially-dispersed measurements to generate realtime information regarding the structure of the local scalar field, which is then used to inform navigation decisions. This article presents initial results of a comprehensive program to develop, verify, and experimentally implement mission-level AN capabilities in three-dimensional (3D) space using our unique multilayer control architecture for groups of vehicles. Using our flexible formation control system, we build upon our prior 2D AN work and provide new contributions to 3D scalar field AN by a) demonstrating a wide range of 3D AN capabilities using a unified, multilayer control architecture, b) extending multivehicle 2D AN control primitives to navigation in 3D scalar fields, and c) introducing state-based sequencing of these primitive AN functions to execute 3D mission-level capabilities such as isosurface mapping and plume following. We verify functionality using high-fidelity simulations of multicopter drone clusters, accounting for vehicle dynamics, outdoor wind gust disturbances, position sensor inaccuracy, and scalar field sensor noise. This paper presents the multilayer architecture for multivehicle formation control, the 3D AN control primitives, the sequencing approaches for specific mission-level capabilities, and simulation results that demonstrate these functions. |
topic |
Adaptive navigation autonomous navigation cluster-space control contour mapping cooperative control extrema seeking |
url |
https://ieeexplore.ieee.org/document/9522136/ |
work_keys_str_mv |
AT robertklee multipleuavadaptivenavigationforthreedimensionalscalarfields AT christopherakitts multipleuavadaptivenavigationforthreedimensionalscalarfields AT michaelaneumann multipleuavadaptivenavigationforthreedimensionalscalarfields AT roberttmcdonald multipleuavadaptivenavigationforthreedimensionalscalarfields |
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1717378599063912448 |