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Autonomous source term estimation in unknown environments: From a dual control concept to UAV deployment

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posted on 2022-01-24, 09:59 authored by Callum Rhodes, Cunjia LiuCunjia Liu, Wen-Hua ChenWen-Hua Chen
In the gas source search and localisation problem, the use of autonomous robots is of increasing interest due to their deployment speed and lack of human interaction with hazardous materials. This paper presents an aerial robotic platform for performing source term estimation of an unknown chemical release in a challenging a-priori unknown and GPS-denied environment. The proposed system forms the search strategy using the state-of-the-art control concept, dual control for exploitation and exploration, and realises such a function in the aforementioned challenging scenario using an RRT* based path planner with a downsampling process to accommodate the computation budget. The proposed algorithm is tested in a high fidelity simulation environment under a number of configurations, and compared against competing algorithms. The system architecture is also brought forward into a bespoke UAV platform and experimentally tested in real-world conditions. The proposed system is shown to be capable of performing source term estimation robustly and efficiently, which provides a step forward in showing the real world application of previously academic functions.

Funding

Engineering and Physical Sciences Research Council (EPSRC) under the project No. 2126619

Goal-Oriented Control Systems (GOCS): Disturbance, Uncertainty and Constraints

Engineering and Physical Sciences Research Council

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History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

IEEE Robotics and Automation Letters

Volume

7

Issue

2

Pages

2274 - 2281

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Version

  • AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Acceptance date

2022-01-04

Publication date

2022-01-20

Copyright date

2022

eISSN

2377-3766

Language

  • en

Depositor

Dr Cunjia Liu. Deposit date: 21 January 2022

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