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How to implement a low level controller? #96
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Hi @HimGautam there already is a subclass of |
Hi @JacopoPan, |
Look at the implementation of
X,Y,Z are transformed into a unit vector that is then multiplied by the 4th parameter. Is this for this project of yours https://github.com/HimGautam/LearningToFly ? |
Hi @JacopoPan, Also I have added small cubes in 3D space to represent the target position in a single episode. But when I change the target position in that episode, the cubes corresponding to previous target are still there and this is making a big mess. So my question is how can I delete the previous target cubes from the simulation. |
The simpler point first, you should be able to remove any URDF you imported into the Bullet scene using W.r.t your results, from what I see on this page https://github.com/HimGautam/LearningToFly I already think you get to a rather interesting policy, seemingly correlated to the positions of the targets. What I note is (1) bias in the positions where the quad stabilizes and (2) oscillations. Because you are using If I were you, I would try a few things: create new target positions/cubes closer to each other, examine the learning policy (when a new cube is created, does it start outputting a vector that connects the current quad position and the new target? Does the 4th value, the magnitude, decreases as the quad approaches the target?), compare to another agent implementation (e.g. PPO). |
Hi @JacopoPan ,
I want to use a reinforcement learning agent for position tracking. My idea is input to RL agent will be X, Y, Z of drone and target and it will output linear velocities. This linear velocity will then be used in a PID controller for low level controller. Can you please tell me how to do this when using your simulator.
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