Hello,

I've got trouble to make SurRol RL env setting. First of all, I was deeply impressed with your SurRol projects.

Here is my problem. I can execute 'needle_pick' and 'needle_regrasp' tasks easily. Then, I want to merge them and learn with Reinforcement Learning.

I divided needle to 18 parts to grab.(This is pybullet env and I pressed 'w' and 'a' key when it execute)

And I want to make,

1. PSM1 grasp needle random point of 18 parts
2. PSM2 regrasp needle random point with RL with stable_baseline3(Cause baseline in github service has been terminated.)

I appreciate if you give me an advice for me. Also, I sent you an email for details.

Best regards, Donghyeon Choi

Hello,

thank you for sharing your repo. I wanted to test it and replicate your results. I have downloaded and installed it. I run the test scripts and everything seems fine. I then checked inside /run where there are three bash script.

I tried to run ddpg_activetrack.sh with the following env id -env=ActiveTrack-v0.

I get the following error:

Traceback (most recent call last):

File "/home/claudia/.pyenv/versions/3.7.12/lib/python3.7/runpy.py", line 193, in _run_module_as_main "main", mod_spec) File "/home/claudia/.pyenv/versions/3.7.12/lib/python3.7/runpy.py", line 85, in _run_code exec(code, run_globals) File "/home/claudia/data/virtual_environments/surrol/lib/python3.7/site-packages/baselines-0.1.6-py3.7.egg/baselines/run.py", line 250, in main(sys.argv) File "/home/claudia/data/virtual_environments/surrol/lib/python3.7/site-packages/baselines-0.1.6-py3.7.egg/baselines/run.py", line 216, in main model, env = train(args, extra_args) File "/home/claudia/data/virtual_environments/surrol/lib/python3.7/site-packages/baselines-0.1.6-py3.7.egg/baselines/run.py", line 54, in train env_type, env_id = get_env_type(args) File "/home/claudia/data/virtual_environments/surrol/lib/python3.7/site-packages/baselines-0.1.6-py3.7.egg/baselines/run.py", line 143, in get_env_type assert env_type is not None, 'env_id {} is not recognized in env types'.format(env_id, _game_envs.keys()) AssertionError: env_id ActiveTrack-v0 is not recognized in env types

Is there a problem with the environment registration in gym?

Following the Issue #662 from Baslines i have add the following line in baselines/run.py at line 52: _game_envs['custom_type'] = { 'ActiveTrack-v0'}

But again i get the following error: gym.error.UnregisteredEnv: No registered env with id: ActiveTrack-v0

Thank you, Cheers Claudia

Hi, @jiaqixuac. This PR aims to fix the bug of running parallel (vectorized) PSM environments. I will explain the cause of the found issue and how to fix that.

When running parallel environments, Pybullet will assign unique object ids to each env. For example, if there is an eval_env (called at first) and a train_env (called at second), which is the case in Stable_baselines3, Pybullet will assign ids of 0-5 to the eval_env and ids of 6-11 to the train_env. Then train_env will store 0-5 into self.obj_ids. Of course, there is no problem when initializing them. However, when you reset those envs through and sample a new goal for the train_env, the function reset(self) will call p.resetSimulation() to reset the simulation. Afterward, Pybullet will assign ids of 0-5 to the train_env. The self.obj_ids of train_env now becomes 0-11. Note that the valid ids are 0-5 now. But in _env_setup(self), the id self.obj_id of the object (like needle) will be set as self.obj_ids['rigid'][0], which belongs to 6-11 (since 0-5 is stored at first, the value at index=0 of the id list is in 0-5). This leads an error pybullet.error: getLinkState failed, since self.obj_id is not contained in the valid ids 0-5.

One possible solution is to reset self.obj_ids along with resetting the simulation. By doing this, we can guarantee that self.obj_id is always in the currently valid objective ids.

Hi, how can i use step function correctly? when i wrote: `import gym import numpy as np from surrol.const import ROOT_DIR_PATH import surrol.gym

env = gym.make("NeedlePick-v0") env.reset() while True: obs = env.step(np.random.randn(5)) env.render()` it gave me an error:

Traceback (most recent call last): File "dato1.py", line 12, in <module> obs = env.step(np.random.randn(5)) File "/home/dato/src/my_projects/robotics/venv/lib/python3.8/site-packages/gym/wrappers/time_limit.py", line 50, in step observation, reward, terminated, truncated, info = self.env.step(action) ValueError: not enough values to unpack (expected 5, got 4) Destroy EGL OpenGL window. how can i fix this?