Project Details
Description
Multiple autonomous vehicle systems (MAVS) have the ability to perform dangerous, repetitive and automated tasks in remote or hazardous environments.
This project aims to address two fundamental research challenges related to the development of novel vision-based coordinated control of multiple autonomous vehicles. The first research challenge is related to real-time image information processing and utilisation, i.e., how to quickly and efficiently extract and analyse image information from consecutive images acquired by the MAVS. The second research challenge is concerned with designing adaptive autonomous vision-based vehicle controllers by exploiting the extracted and analysed image information to cooperatively control the MAVS, and also improve the MAVS’s capabilities, such as control and tracking, etc.
Funded by the The Royal Society of Edinburgh (RSE), £12,000
This project aims to address two fundamental research challenges related to the development of novel vision-based coordinated control of multiple autonomous vehicles. The first research challenge is related to real-time image information processing and utilisation, i.e., how to quickly and efficiently extract and analyse image information from consecutive images acquired by the MAVS. The second research challenge is concerned with designing adaptive autonomous vision-based vehicle controllers by exploiting the extracted and analysed image information to cooperatively control the MAVS, and also improve the MAVS’s capabilities, such as control and tracking, etc.
Funded by the The Royal Society of Edinburgh (RSE), £12,000
Notes
Funded by the The Royal Society of Edinburgh (RSE), £12,000
| Status | Finished |
|---|---|
| Effective start/end date | 1/05/12 → 30/06/15 |
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