Confusion about Train Humanoid Walker

I'm using MATLAB's example "Train Humanoid Walker" without changing any parameters or weights. I expected to train the robot to walk smoothly, but even after training for over 10,000 episodes, the best result I achieved was just one step of movement. What adjustments can I make to ensure the humanoid robot walks properly? Thanks a lot for your help.

[Aquatris]

If you are using the GA approach, increasing the reward for forward velocity and decreasing the penalty for power consumption should give you better motion.

Answer 1

[Shubham]

Hi James,

Training a humanoid robot to walk smoothly in MATLAB can be quite challenging due to the complexity of the task. Here are some adjustments and strategies you can consider to improve the training process:

• Ensure that the reward function strongly encourages forward movement and penalizes falling or unstable behavior. You can add a reward for maintaining balance and a penalty for actions that lead to falling.
• Adjust the learning rate. If it's too high, the training might be unstable; if it's too low, the training might be too slow.
• Modify the discount factor to balance immediate and future rewards.
• Ensure that the exploration rate (epsilon in epsilon-greedy policies) starts high and gradually decreases to allow the agent to explore the environment adequately before exploiting learned behaviors.
• Increase the maximum number of steps per episode. This allows the robot more time to learn how to walk properly within each episode.
• Start with simpler tasks and gradually increase the difficulty. For example, start by training the robot to balance in place, then take a single step, and gradually increase the number of steps.
• Sometimes, more training time is needed. Ensure that the training process runs for enough episodes to allow the agent to learn effectively.

By carefully adjusting these parameters and strategies, you should be able to improve the training process and achieve smoother walking behavior for your humanoid robot.