Training Quadrotor using PPO agent
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So I am trying to control a quadrotor model using Reinforcement learning. My agent will control my quadrotor and make it navigating to a desired position or following a path. Right now I am trying to train my PPO agent to hover the quadrotor. I built a dynamical model of the quadrotor with 6DOF block. After that I built the observation and reward function of my agent.
I coded the actor critic network and set my parameters.The problem is my reward function is always equals to 0 and my agent is not learning and I am suspuscious that I didn't build the environment correctly. I have been working on my model for long period and couldn't make my agent learn a little. I will really be glad if someone can support me on this issue.
I attached my quadrotor Reinforcement learning model with actor and critic codes.

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Unmanned Aerial and Space Systems
2022년 5월 2일
Hi, is there a solution for your problem, in my model, there is a same problem. I shared below:
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Emmanouil Tzorakoleftherakis
2022년 4월 28일
편집: Emmanouil Tzorakoleftherakis
2022년 4월 28일
Hello,
There are multiple things not set up properly, including:
1) The isdone flag seems to be 1 all the time leading to episodes terminating early, after a single step
2) The reward signal is often not a scalar real number. One reason is that you are trying to calculate the sq root of a negative number
3) Your Simulink model has a lot of algebraic loops - I would get rid of those to make sure they don't interfere with training.
Hope that helps
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Unmanned Aerial and Space Systems
2025년 8월 3일
Hi Dear Salman, It seems a while since I posted this query.
If you can help us to fix this problem, we can go through the model and problem, thanks.
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