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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ge Yang Rubo Zhang |
| Copyright Year | 2009 |
| Abstract | This paper proposes an adapted inertia-weight particle swarm optimal algorithm (AIPSO) for path planning of an autonomous underwater vehicle in a sea field environment characterized by strong currents. The goal is to find a safe path that takes the vehicle from its starting location to a mission-specified destination, while minimizing the energy cost. The PSO algorithm used here introduced a self-adapted inertia weight factor to speed up the convergence to the global minimum. The method is proved to be effective in simulation experiments. The proposed algorithm can make AUV travel longer and save more energy comparing to tradition path planning methods. |
| Starting Page | 299 |
| Ending Page | 302 |
| File Size | 997465 |
| Page Count | 4 |
| File Format | |
| ISBN | 9780769537368 |
| DOI | 10.1109/ICNC.2009.355 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-08-14 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Marine technology adapted inertia-weight PSO Virtual colonoscopy Costs AUV Oceans Sea measurements Educational institutions Path planning path planning Underwater vehicles Remotely operated vehicles Computer science current |
| Content Type | Text |
| Resource Type | Article |
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