Hello Harry,
I tried to replicate the RL example in the GitHub link you shared, but I
have been trying to fix the following error. It seems the pychrono.parsers
module is missing.
Traceback (most recent call last):
File
"C:\Users\chike\Box\TurtleRobotExperiments\Sea_Turtle_Robot_AI_Powered_Simulations_Project\NnamdiFiles\mujocotest1\chrono\multi-terrain-RL\rl_examples\rslrl\eval.py",
line 8, in <module>
from chrono_env import ChronoQuadrupedEnv as RigidTerrainEnv
File
"C:\Users\chike\Box\TurtleRobotExperiments\Sea_Turtle_Robot_AI_Powered_Simulations_Project\NnamdiFiles\mujocotest1\chrono\multi-terrain-RL\rl_examples\rslrl\chrono_env.py",
line 13, in <module>
import simulation.Robots as Robots
File
"C:\Users\chike\Box\TurtleRobotExperiments\Sea_Turtle_Robot_AI_Powered_Simulations_Project\NnamdiFiles\mujocotest1\chrono\multi-terrain-RL\simulation\Robots.py",
line 7, in <module>
import pychrono.parsers as parsers
ModuleNotFoundError: No module named 'pychrono.parsers'
Could you please provide some help with this? I followed
conda create -n chrono "python<3.13" -c conda-forge conda activate chrono
conda install bochengzou::pychrono -c bochengzou -c nvidia -c dlr-sc -c
conda-forge
Install RL Library
<https://github.com/uwsbel/sbel-reproducibility/tree/master/2025/multi-terrain-RL#install-rl-library>
Inside the conda environment, supposingly named as chrono:
pip install rsl-rl-lib==2.2.4
Verify Installation
<https://github.com/uwsbel/sbel-reproducibility/tree/master/2025/multi-terrain-RL#verify-installation>
Inside the conda environment:
cd <path_to_current_folder>/multi-terrain-RL python
rl_examples/rslrl/eval.py --ckpt 2999
Best regards,
Nnamdi
On Monday, August 4, 2025 at 3:57:30 PM UTC-4 [email protected] wrote:
> Hello Nnamdi,
>
> I hope you are doing well.
>
> I want to share this repo (
> https://github.com/uwsbel/sbel-reproducibility/tree/master/2025/multi-terrain-RL)
>
> with you, which does the RL training for the demo videos I shared earlier.
> The specific robot type or task might differ, but I think the structure or
> idea would be similar.
>
> I realize I previously offered to meet, but after giving it more
> thought—and in light of similar requests from others—We’ve decided it's
> better to share a prepared code repo instead. This way, you can try it on
> your own and post any questions here, so others can also benefit from the
> discussion.
>
> Best,
> Harry
>
> On Wednesday, July 30, 2025 at 7:50:49 PM UTC-5 [email protected] wrote:
>
>> Hello Harry,
>>
>> Your simulation results looks great and are similar to what I hope to
>> implement in my setup. I am interested in discussing more about this and
>> would love to set up a meeting as soon as possible. Can you please let me
>> know what day/time you are available?
>>
>> Best regards,
>> Nnamdi
>>
>> On Wednesday, July 30, 2025 at 1:50:56 PM UTC-4 [email protected] wrote:
>>
>>> Picture attachment for last message:
>>> [image: Screenshot from 2025-07-30 10-45-41.png]
>>> Best,
>>> Harry
>>> On Wednesday, July 30, 2025 at 11:17:42 AM UTC-5 Harry ZHANG wrote:
>>>
>>>> Hello Nnamdi,
>>>>
>>>> My name's Harry and Dan asked me to follow up on this thread.
>>>>
>>>> About couple weeks ago, we start exploring using PyChrono as our
>>>> physics engine to train RL policies for quadruped locomotion task. Our
>>>> projects's goal is to investigate simulation terrain's effect on
>>>> locomotion
>>>> policy performance. In PyChrono there are different fidelity levels for
>>>> terrain model (from low to high): rigid terrain (rtf<<1) --> SCM
>>>> deformable
>>>> terrain (rtf~=1)-->CRM granular terrain(rtf~=5), where rtf means real time
>>>> fator. RL library we are using is "RSL-RL".
>>>>
>>>> Please check this link for prelim results we got:
>>>> https://drive.google.com/drive/folders/1Yhx1goYDsv0FZdk4OfyH9_yRazkRSwMQ?usp=sharing.
>>>>
>>>> The locomotion policy trained for 0.5 m/s longitudinal speed walking. The
>>>> policy trained with rigid terrain (about 6 hours) and we put it on scm
>>>> deformable terrain for testing purpose, in both rigid and deformable
>>>> terrain the evaluation looks decent.
>>>>
>>>> For us, there are two major things in our todo list: 1) implement some
>>>> parallelzation methods during training. current 6 hour training time is
>>>> trained with one single simulation agent interact with RSL-RL algorithm,
>>>> we
>>>> try to see if it's possible to do faster by training with multiple
>>>> simulation agents. 2) Include quadrupeds with CRM terrain in both policy
>>>> training and evaluation. See the attched picture, we have a simulation
>>>> script includes quadrupeds on CRM terrain, but we need to merge this into
>>>> RL pipeline.
>>>>
>>>> Let me know if you have any questions, I am available for meeting if
>>>> you want me explain more about the pipeline and details.
>>>>
>>>> Best,
>>>> Harry
>>>>
>>>> On Monday, July 28, 2025 at 4:40:48 PM UTC-5 [email protected] wrote:
>>>>
>>>>> Thank you so much for your response.
>>>>>
>>>>> We are starting to work in this area as well, from a slightly
>>>>> different perspective. Harry, a great student in the lab, will share his
>>>>> findings in about a week, to steer you in the right direction. Are you
>>>>> working with a quadruped or something similar?
>>>>>
>>>>> I am working on a small-sized bioinspired quadruped robot, and I look
>>>>> forward to the findings from your student.
>>>>>
>>>>> Is it like (a) the entire terrain is made up of rocks 2cm to 6 cm, or
>>>>> (b) you have some deformable terrain that once in a while has some rocks
>>>>> 2
>>>>> cm to 6 cm scattered around? This is important, since (a) will likely
>>>>> take
>>>>> more time to run than (b).
>>>>>
>>>>> I am interested in having the entire terrain composed of movable
>>>>> rocks, which the limbs can interact with, such as each terrain box filled
>>>>> with rocks of a specific size (2cm to 6cm). I am also open to suggestions
>>>>> on whether this setup might be computationally intensive and any
>>>>> alternatives, such as option B. The image below is what I have in mind
>>>>> (generated in MuJoCo, but is fixed to the ground)
>>>>> [image: Screenshot 2025-07-28 172945.png]
>>>>>
>>>>> In principle, this should be doable but we haven’t tried it yet. The
>>>>> needed modeling elements are in Chrono, it’s just a matter of putting a
>>>>> model like this together and seeing how it does. Easier said than done,
>>>>> but
>>>>> we might be able to provide some feedback when you cross that bridge.
>>>>>
>>>>> Thank you. I will provide more details on my proposed implementation
>>>>> soon.
>>>>>
>>>>> In about one week we’ll share a way to install a newer version of
>>>>> PyChrono, a beta version, that has support for what’s called in Chrono
>>>>> “the
>>>>> CRM terrain” model. Might be helpful for you. Needs an NVIDIA GPU to run.
>>>>>
>>>>> Looking forward to the new version. I have been facing some SDL2
>>>>> package errors with my current version. I gave more details in a
>>>>> different
>>>>> thread.
>>>>> On Thursday, July 24, 2025 at 3:53:14 PM UTC-4 Dan Negrut wrote:
>>>>>
>>>>>> Please see my comments in this font below.
>>>>>>
>>>>>>
>>>>>>
>>>>>> Thank you,
>>>>>>
>>>>>> Dan
>>>>>>
>>>>>> ---------------------------------------------
>>>>>>
>>>>>> Bernard A. and Frances M. Weideman Professor
>>>>>>
>>>>>> NVIDIA CUDA Fellow
>>>>>>
>>>>>> Department of Mechanical Engineering
>>>>>>
>>>>>> Department of Computer Science
>>>>>>
>>>>>> University of Wisconsin - Madison
>>>>>>
>>>>>> 4150ME, 1513 University Avenue
>>>>>>
>>>>>> Madison, WI 53706-1572
>>>>>>
>>>>>> 608 772 0914 <(608)%20772-0914>
>>>>>>
>>>>>> http://sbel.wisc.edu/
>>>>>>
>>>>>> http://projectchrono.org/
>>>>>>
>>>>>> ---------------------------------------------
>>>>>>
>>>>>>
>>>>>>
>>>>>> *From:* Nnamdi Chikere <[email protected]>
>>>>>> *Sent:* Thursday, July 24, 2025 10:31 AM
>>>>>> *To:* Dan Negrut <[email protected]>
>>>>>> *Cc:* ProjectChrono <[email protected]>
>>>>>> *Subject:* Re: [chrono] Help with Granular Simulation on Windows
>>>>>> using PyChrono
>>>>>>
>>>>>>
>>>>>>
>>>>>> Hello Professor,
>>>>>>
>>>>>>
>>>>>>
>>>>>> Thank you so much for your reply.
>>>>>>
>>>>>>
>>>>>>
>>>>>> For the first stage, I am trying to optimize the parameters for
>>>>>> control of the robot’s locomotion on complex environments including sand
>>>>>> and rocks using CPGs. The end goal is to later use RL to implement
>>>>>> adaptive
>>>>>> control with changing terrains.
>>>>>>
>>>>>> We are starting to work in this area as well, from a slightly
>>>>>> different perspective. Harry, a great student in the lab, will share his
>>>>>> findings in about a week, to steer you in the right direction. Are you
>>>>>> working with a quadruped or something similar?
>>>>>>
>>>>>>
>>>>>>
>>>>>> For the rock sizes, I was looking to implement three rock sizes
>>>>>> ranging between 2cm and 6cm filled in a box on which the robot will
>>>>>> operate.
>>>>>>
>>>>>> Is it like (a) the entire terrain is made up of rocks 2cm to 6 cm; or
>>>>>> (b) you have some deformable terrain that once in a while has some rocks
>>>>>> 2
>>>>>> cm to 6 cm scattered around? This is important, since (a) will likely
>>>>>> take
>>>>>> more time to run than (b).
>>>>>>
>>>>>>
>>>>>>
>>>>>> I am also trying to implement a flexible limb that will be attached
>>>>>> to the motors and deform when in contact with some force or the ground,
>>>>>> is
>>>>>> it possible to implement this to a specified link?
>>>>>>
>>>>>> In principle, this should be doable but we haven’t tried it yet. The
>>>>>> needed modeling elements are in Chrono, it’s just a matter of putting a
>>>>>> model like this together and seeing how it does. Easier said than done,
>>>>>> but
>>>>>> we might be able to provide some feedback when you cross that bridge.
>>>>>>
>>>>>>
>>>>>>
>>>>>> I am working with Python and windows, and would appreciate some help
>>>>>> as regards this
>>>>>>
>>>>>> In about one week we’ll share a way to install a newer version of
>>>>>> PyChrono, a beta version, that has support for what’s called in Chrono
>>>>>> “the
>>>>>> CRM terrain” model. Might be helpful for you. Needs an NVIDIA GPU to run.
>>>>>>
>>>>>>
>>>>>>
>>>>>> Best regards,
>>>>>>
>>>>>> Nnamdi
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Thu, Jul 24, 2025 at 2:10 AM Dan Negrut <[email protected]> wrote:
>>>>>>
>>>>>> If you describe what you need to do with your robot, we might be able
>>>>>> to steer you in the right direction.
>>>>>> How big are the rocks you mentioned?
>>>>>>
>>>>>> What sort of end-goal do you have? Design of robot, control of robot,
>>>>>> RL, optimal design, etc.
>>>>>>
>>>>>>
>>>>>>
>>>>>> Dan
>>>>>>
>>>>>> ---------------------------------------------
>>>>>>
>>>>>> Bernard A. and Frances M. Weideman Professor
>>>>>>
>>>>>> NVIDIA CUDA Fellow
>>>>>>
>>>>>> Department of Mechanical Engineering
>>>>>>
>>>>>> Department of Computer Science
>>>>>>
>>>>>> University of Wisconsin - Madison
>>>>>>
>>>>>> 4150ME, 1513 University Avenue
>>>>>> <https://urldefense.com/v3/__https:/www.google.com/maps/search/1513*University*Avenue**A0D*0A*Madison,*WI*53706-1572?entry=gmail&source=g__;KysrJSUrKys!!Mak6IKo!Od8BEUkPpm5WoEens9KtQIg47iogD1i2m9LDYGHeEv2M8GiWuVl9N0Stk5HjyF-DIbSFX75lMxV4hhD5$>
>>>>>>
>>>>>> Madison, WI 53706-1572
>>>>>> <https://urldefense.com/v3/__https:/www.google.com/maps/search/1513*University*Avenue**A0D*0A*Madison,*WI*53706-1572?entry=gmail&source=g__;KysrJSUrKys!!Mak6IKo!Od8BEUkPpm5WoEens9KtQIg47iogD1i2m9LDYGHeEv2M8GiWuVl9N0Stk5HjyF-DIbSFX75lMxV4hhD5$>
>>>>>>
>>>>>> 608 772 0914 <(608)%20772-0914>
>>>>>>
>>>>>> http://sbel.wisc.edu/
>>>>>>
>>>>>> http://projectchrono.org/
>>>>>> <https://urldefense.com/v3/__http:/projectchrono.org/__;!!Mak6IKo!Od8BEUkPpm5WoEens9KtQIg47iogD1i2m9LDYGHeEv2M8GiWuVl9N0Stk5HjyF-DIbSFX75lM0FtMmwz$>
>>>>>>
>>>>>>
>>>>>> ---------------------------------------------
>>>>>>
>>>>>>
>>>>>>
>>>>>> *From:* 'Nnamdi Chikere' via ProjectChrono <
>>>>>> [email protected]>
>>>>>> *Sent:* Tuesday, July 22, 2025 6:16 PM
>>>>>> *To:* ProjectChrono <[email protected]>
>>>>>> *Subject:* [chrono] Help with Granular Simulation on Windows using
>>>>>> PyChrono
>>>>>>
>>>>>>
>>>>>>
>>>>>> Hello.
>>>>>>
>>>>>> I am working on a simulation where a robot moves on different
>>>>>> terrains, and I want to simulate the robot moving on sand and rocks. I
>>>>>> have
>>>>>> been able to implement the soil terrain using the SCM parameters in
>>>>>> PyChrono. Is it possible to implement granular media, such as rocks, in
>>>>>> PyChrono? I attempted to install the DEME package, but encountered
>>>>>> several
>>>>>> errors. I am working with PyChrono 9.0 and Python 3.9.
>>>>>>
>>>>>> Thank you.
>>>>>>
>>>>>> --
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>>>>>> Groups "ProjectChrono" group.
>>>>>> To unsubscribe from this group and stop receiving emails from it,
>>>>>> send an email to [email protected].
>>>>>> To view this discussion visit
>>>>>> https://groups.google.com/d/msgid/projectchrono/d38be8a1-f6e0-4661-83ba-d51b500ccea5n%40googlegroups.com
>>>>>>
>>>>>> <https://urldefense.com/v3/__https:/groups.google.com/d/msgid/projectchrono/d38be8a1-f6e0-4661-83ba-d51b500ccea5n*40googlegroups.com?utm_medium=email&utm_source=footer__;JQ!!Mak6IKo!IHl25Nn94rVvk-8cbLYWCsyZEpu7zcoKd_JY1u7_ZFpAebs2_ga8vymx9iyQT1Ywjzy8INBVzHAHobmHZEkRFozUi6s$>
>>>>>> .
>>>>>>
>>>>>>
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