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PATH PLANNING FOR THE HYBRID AERIAL UNDERWATER ROBOTIC SYSTEM
| Title: | PATH PLANNING FOR THE HYBRID AERIAL UNDERWATER ROBOTIC SYSTEM. |
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| Name(s): |
Davis, Anthony C. , author Ouyang, Bing , Thesis advisor Florida Atlantic University, Degree grantor Department of Computer and Electrical Engineering and Computer Science College of Engineering and Computer Science |
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| Type of Resource: | text | |
| Genre: | Electronic Thesis Or Dissertation | |
| Date Created: | 2022 | |
| Date Issued: | 2022 | |
| Publisher: | Florida Atlantic University | |
| Place of Publication: | Boca Raton, Fla. | |
| Physical Form: | application/pdf | |
| Extent: | 68 p. | |
| Language(s): | English | |
| Abstract/Description: | Marine food chains are highly stressed by aggressive fishing practices and environmental damage. Aquaculture has increasingly become a source of seafood which spares the deleterious impact to wild fisheries, but it requires continuous water quality data to successfully grow and harvest fish. Aerial drones have great potential to monitor large areas quickly and efficiently. The Hybrid Aerial Underwater Robotic System (HAUCS) is a swarm of unmanned aerial vehicles (UAVs) and underwater measurement devices designed to collect water quality data of aquaculture ponds. The routing of drones to cover each fish pond on an aquaculture farm can be reduced to the Vehicle Routing Problem (VRP). A dataset is created to simulate the distribution of ponds on a farm and is used to assess the HAUCS Path Planning Algorithm (HPP). Its performance is compared with the Google Linear Optimization Package (GLOP) and a Graph Attention Model (GAM) for routing around the simulated farms. The three methods are then implemented on a team of waterproof drones and experimentally verified at Southern Illinois University’s (SIU) Aquaculture Research Center. GLOP and GAM are demonstrated to be efficient path planning methods for small farms, while HPP is likely to be more suited to large farms. HAUCS shows great value as a future direction for intelligent aquaculture, but issues with obstacle avoidance and robust waterproofing need to be addressed before commercialization. The future of aquaculture promises more integrated and sustainable operations by mimicking natural systems and leveraging deeper understandings of biology. | |
| Identifier: | FA00014108 (IID) | |
| Degree granted: | Thesis (MS)--Florida Atlantic University, 2022. | |
| Collection: | FAU Electronic Theses and Dissertations Collection | |
| Note(s): | Includes bibliography. | |
| Subject(s): |
Drone aircraft Drones Aquaculture |
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| Persistent Link to This Record: | http://purl.flvc.org/fau/fd/FA00014108 | |
| Use and Reproduction: | Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder. | |
| Host Institution: | FAU | |
| Is Part of Series: | Florida Atlantic University Digital Library Collections. |
