Underwater robotic vehicles are used in a variety of environments that would be dangerous for humans. For these vehicles to be successful, they need to be tolerant of a variety of internal and external faults. To be resilient to internal faults, the system must be capable of determining the source of faulty behavior. However many different faults within a robotic vehicle can create identical faulty behavior, which makes the vehicles impossible to diagnose using conventional methods. I propose a novel active diagnosis method for differentiating between faults that would otherwise have identical behavior. I apply this method to a communication system and a power distribution system in a robotic vehicle and show that active diagnosis is successful in diagnosing partially observable faults. An example of an external fault is inter-robot communication in underwater robotics. The primary communication method for underwater vehicles is acoustic communication which relies heavily on line-of-sight tracking and range. This can cause severe packet loss between agents when a vehicle is operating around obstacles. I propose novel path-planning methods for an Autonomous Underwater Vehicle (AUV) that ferries messages between agents. I applied this method to a custom underwater simulator and illustrate how it can be used to preserve at least twice as many packets sent between agents than would be obtained using conventional methods.
| Identifer | oai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-10767 |
| Date | 02 December 2022 |
| Creators | Webb, Devon M. |
| Publisher | BYU ScholarsArchive |
| Source Sets | Brigham Young University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | https://lib.byu.edu/about/copyright/ |
Page generated in 0.0014 seconds