Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/4539
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mahapatro, Abhijit | - |
dc.contributor.author | Parhi, Dayal R | - |
dc.date.accessioned | 2024-04-16T05:45:13Z | - |
dc.date.available | 2024-04-16T05:45:13Z | - |
dc.date.issued | 2024-03 | - |
dc.identifier.citation | 4th International Conference on River Corridor Research and Management (RCRM), IIT Jammu, India, 7-9 March 2024 | en_US |
dc.identifier.uri | http://hdl.handle.net/2080/4539 | - |
dc.description | Copyright belongs to proceeding publisher | en_US |
dc.description.abstract | Path planning with obstacle avoidance is crucial for navigating an Autonomous Underwater Vehicle (AUV) in an unknown and obstacle-rich three-dimensional space. Many studies have been conducted to develop a controller that can effectively navigate through an obstacle-rich environment for a mobile robot in a two-dimensional terrain. However, the trajectory planning of AUVs in a three-dimensional environment is still challenging. This paper aims to develop an optimized obstacle-free path in a three-dimensional environment using a modified Tuna Swarm Optimization (MTSO) technique. There are four techniques in TSO; each is selected based on the requirement and independent of the other. This proposed MTSO controller is tested under laboratory and computer simulation to determine its effectiveness. Less than 5% deviation is noticed between them due to signal delay and hydrodynamic effect on the AUV. | en_US |
dc.subject | Autonomous Underwater Vehicle | en_US |
dc.subject | Tuna Swarm Optimization | en_US |
dc.subject | Path Planning | en_US |
dc.subject | Navigation | en_US |
dc.subject | Optimization | en_US |
dc.title | Analysis of Modified Tuna Swarm Optimization Technique for Path Planning of Underwater Vehicle | en_US |
dc.type | Presentation | en_US |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
2024_ICRCRM_AMahapatro_Analysis.pdf | Presentation | 1.96 MB | Adobe PDF | View/Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.