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About Design of Deep Reinforcement Learning Controller Through Data Assisted Model For Robotic Fish Speed Tracking
This document describes a study that used deep reinforcement learning to control the speed of a robotic fish. Experimental data was collected from a 3D printed robotic fish and used to build a data-assisted model of the fish's dynamics. A genetic algorithm was then used to estimate influential parameters in the model. A deep reinforcement learning controller called TD3 was trained in simulations using this model to track desired speeds. The TD3 controller was able to learn effective control policies and outperformed alternative controllers like DDPG and PID in tracking speed under different disturbances.
Detailed Information
| Author: | ['hadi'] |
|---|---|
| Publication Year: | 2023 |
| Pages: | 14 |
| Language: | English |
| Format: | |
| Price: | FREE |
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