Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.
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Sir, could you provide a trained model? please #161
hello, sir!I have some trouble with training.
why it is hard to train a well model with you origin code.
I have run the train_velodyne_td3.py for a half of day with nvidia GPU: RTX 3060. but the robot still can not navigate to its goal.
can you tell me how long to run to get a well model.
the following pic is the loss and Q value, The loss fluctuates greatly. Is this normal?
Please help me ! Thanks !
hello, sir!I have some trouble with training. why it is hard to train a well model with you origin code. I have run the
train_velodyne_td3.py
for a half of day with nvidia GPU: RTX 3060. but the robot still can not navigate to its goal. can you tell me how long to run to get a well model. the following pic is the loss and Q value, The loss fluctuates greatly. Is this normal? Please help me ! Thanks !