Simulation of Semantically-Aware Obstacle Avoidance Algorithms for Underwater Robots

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Simulation of Semantically-Aware Obstacle Avoidance Algorithms for Underwater Robots

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Researchers working with autonomous underwater vehicles (AUVs) must be able to test their robotic vision-based algorithms on-location in field trials. These trials can be time-consuming and carry the risk of unforeseen hardware and software bugs limiting the amount of data gathered. To this end, being able to test and evaluate algorithms risk-free in a computer simulation beforehand can be invaluable for researchers. Current simulation solutions can provide realistic physics and easily modifiable worlds, however using a 3D graphics engine to create realistic underwater scenarios can improve results considerably and ease the transition into a real-world environment. This research demonstrates the potential of the Unity 3D graphics engine to provide a realistic simulation environment by running and evaluating a vision-based underwater obstacle avoidance algorithm on a simulated Aqua robot. We find that Unity can provide simulated stereo images that can be used by the Semantic Obstacle Avoidance for Robots (SOAR) algorithm to navigate a simple obstacle field en route to a predetermined goal position.


Faculty Advisor: Junaed Sattar

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This research was supported by the Undergraduate Research Opportunities Program (UROP).

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Walaszek, Chris A. (2021). Simulation of Semantically-Aware Obstacle Avoidance Algorithms for Underwater Robots. Retrieved from the University Digital Conservancy,

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