| EPSRC Reference: |
EP/I012923/1 |
| Title: |
An Intelligent Integrated Navigation and Autopilot System for Uninhabited Surface Vehicles |
| Principal Investigator: |
Sutton, Professor R |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Sch of Marine Science & Engineering |
| Organisation: |
University of Plymouth |
| Scheme: |
Standard Research |
| Starts: |
01 April 2011 |
Ends: |
30 September 2014 |
Value (£): |
354,231
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Control Engineering |
| Image & Vision Computing |
Robotics & Autonomy |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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03 Nov 2010
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Materials, Mechanical and Medical Engineering
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Announced
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Summary on Grant Application Form |
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Global positioning systems (GPSs) are very useful navigational aids for both civilian and military vehicular systems. However, owing to the weakness of the radio signals from the satellites they are susceptible to signal loss when operations are being conducted in confined areas such as rivers, mountains and canyons, and are extremely exposed to being deliberately jammed by terrorists or aggressors during times of extreme tension or conflict. Thus given the vulnerability of GPSs to signal loss, it is prudent not to be totally reliant upon them in the design of navigation subsystems for autonomous vehicles (AVs). One solution to this problem is to enhance the subsystem with an algorithm based on simultaneous localization and mapping (SLAM) techniques. SLAM being the process of simultaneously building a feature based map of the operating environment and utilizing it to estimate the location of an AV. To further improve the capability and performance envelope of an AV it is appropriate to combine a SLAM reinforced navigation subsystem with an adaptive control subsystem thereby transforming them into one fully integrated system.This research proposal aims to design and build a new advanced intelligent integrated navigation and autopilot (IINA) system with adaptive capabilities for uninhabited surface vehicles (USVs). The existing intelligent navigation (IN) subsystem will be complemented with a SLAM algorithm which will be newly designed and also capable of interfacing with other types of more traditional navigation system. The new improved IN subsystem will be benchmarked against the existing navigation subsystem and a navigation system enhanced with an inertial measurement unit supplied by Atlantic Inertial Systems (AIS) who are the industrial collaborator for this project. Whilst the intelligent integrated system will be designed and developed for a marine application, the technology evolved will be able to be transferred and used in other types of AV.A common feature with many SLAM algorithms is the reliance upon extended Kalman filters to act as the information data collection mechanism. In this research proposal an interval Kalman filter (IKF) which uses interval calculus in its design will be employed instead and enhanced using artificial intelligence techniques to construct a fuzzy IKF (FIKF). Scene information extraction for SLAM can be from visual or non-visual sources. Visual SLAM has the benefit of selecting and using robust features gained from video imagery of the local scene. A novel aspect of this work will be the design of a feature-matching algorithm (FMA) that will be capable of operating in night-time conditions. Thus, an information data collection mechanism based on a FIKF will be integrated with the FMA to form the overall SLAM enhancement algorithm.Whilst there are a number of methods for introducing adaptability into an autopilot design, in this research project the approach to be taken will be based on a combination of on-line closed loop identification and model predictive control. Thus the methodology described herein represents a new conceptual framework for the design of marine autopilots. It should also be noted that, to date, all uninhabited marine vehicle system identification trials have been performed in the open loop. Upon the successful completion of the design of the adaptive autopilot, it will be merged with the SLAM enhanced IN subsystem to form the IINA system.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.plym.ac.uk |