Fine Tuning Swimming Locomotion Learned from Mosquito Larvae

• URL: http://arxiv.org/abs/2412.02702v1
• Date: Sat, 16 Nov 2024 06:54:43 GMT
• Title: Fine Tuning Swimming Locomotion Learned from Mosquito Larvae
• Authors: Pranav Rajbhandari, Karthick Dhileep, Sridhar Ravi, Donald Sofge,
• Abstract summary: In prior research, we analyzed the backwards swimming motion of mosquito larvae, parameterized it, and replicated it in a Computational Fluid Dynamics (CFD) model.<n>In this project, we further optimize this copied solution for the model of the swimmer.
• Score: 0.9349784561232036
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In prior research, we analyzed the backwards swimming motion of mosquito larvae, parameterized it, and replicated it in a Computational Fluid Dynamics (CFD) model. Since the parameterized swimming motion is copied from observed larvae, it is not necessarily the most efficient locomotion for the model of the swimmer. In this project, we further optimize this copied solution for the swimmer model. We utilize Reinforcement Learning to guide local parameter updates. Since the majority of the computation cost arises from the CFD model, we additionally train a deep learning model to replicate the forces acting on the swimmer model. We find that this method is effective at performing local search to improve the parameterized swimming locomotion.

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