Environmental Feature Exploration with a Single Autonomous Vehicle
- Submitting institution
-
University of Exeter
- Unit of assessment
- 12 - Engineering
- Output identifier
- 2138
- Type
- D - Journal article
- DOI
-
10.1109/TCST.2019.2908141
- Title of journal
- IEEE Transactions on Control Systems Technology
- Article number
- -
- First page
- 1349
- Volume
- 28
- Issue
- 4
- ISSN
- 1063-6536
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
D - Dynamics and Control
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is a key output of the SBRI Innovate UK project "Adaptive Autonomous Ocean Sampling" (£500K). It is the output of a collaboration between UoE, the engineering company L3 ASV and the Scottish Association for Marine Science (SAMS). It describes an algorithm to autonomously explore sea surface phenomenon in a more efficient way than existing 'lawn-mower' approaches and is the subject of a patent application (PCT/GB2017/0519190). This technology was instrumental in UoE's invitation to be involved in the NERC funded CAMPUS project led by PML (NE/R006768/1 £315K) which seeks to deliver an improved evidence-base for ecosystem marine management.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -