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
Inside the conda environment, supposingly named as chrono:
pip install rsl-rl-lib==2.2.4
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
<https://urldefense.com/v3/__https://github.com/uwsbel/sbel-reproducibility/tree/master/2025/multi-terrain-RL__;!!Mak6IKo!NNZn_b2z9W4LO4J581E-MjNPOiP3Ycu6Aq4Tl1QDCtM_LLuFYDaL6-RQ1C6nAeNfanFjXrRNIOIfwQNCC_e1hx3XANFT5w$>)
with you, which does the RL training for the demo videos I
shared earlier. The specific robot type or task might
differ, but I think the structure or idea would be similar.
I realize I previously offered to meet, but after giving it
more thought—and in light of similar requests from
others—We’ve decided it's better to share a prepared code
repo instead. This way, you can try it on your own and post
any questions here, so others can also benefit from the
discussion.
Best,
Harry
On Wednesday, July 30, 2025 at 7:50:49 PM UTC-5
[email protected] wrote:
Hello Harry,
Your simulation results looks great and are similar to
what I hope to implement in my setup. I am interested in
discussing more about this and would love to set up a
meeting as soon as possible. Can you please let me know
what day/time you are available?
Best regards,
Nnamdi
On Wednesday, July 30, 2025 at 1:50:56 PM UTC-4
[email protected] wrote:
Picture attachment for last message:
Screenshot from 2025-07-30 10-45-41.png
Best,
Harry
On Wednesday, July 30, 2025 at 11:17:42 AM UTC-5
Harry ZHANG wrote:
Hello Nnamdi,
My name's Harry and Dan asked me to follow up on
this thread.
About couple weeks ago, we start exploring using
PyChrono as our physics engine to train RL
policies for quadruped locomotion task. Our
projects's goal is to investigate simulation
terrain's effect on locomotion policy
performance. In PyChrono there are different
fidelity levels for terrain model (from low to
high): rigid terrain (rtf<<1) --> SCM deformable
terrain (rtf~=1)-->CRM granular terrain(rtf~=5),
where rtf means real time fator. RL library we
are using is "RSL-RL".
Please check this link for prelim results we
got:
https://drive.google.com/drive/folders/1Yhx1goYDsv0FZdk4OfyH9_yRazkRSwMQ?usp=sharing
<https://urldefense.com/v3/__https://drive.google.com/drive/folders/1Yhx1goYDsv0FZdk4OfyH9_yRazkRSwMQ?usp=sharing__;!!Mak6IKo!NNZn_b2z9W4LO4J581E-MjNPOiP3Ycu6Aq4Tl1QDCtM_LLuFYDaL6-RQ1C6nAeNfanFjXrRNIOIfwQNCC_e1hx2HrX2Chw$>.
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)
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
<https://urldefense.com/v3/__https://www.google.com/maps/search/1513*0D*0A**mUniversity*Avenue**A0D*0A**jMadison,*WI*0D*0A**m53706-1572?entry=gmail&source=g__;JSUrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKyslJSsrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrJSUrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysr!!Mak6IKo!KdbaCCLAD5Cq61HUQ4b5JCrg7PjBvB9hSNDyV7cu1Dz_BxVbT-BX3ViQuoDj3YUdNbSnchnKWHwuzYJmLBg$>
<https://urldefense.com/v3/__https://www.google.com/maps/search/1513*0D*0A**mUniversity*Avenue**A0D*0A**jMadison,*WI*0D*0A**m53706-1572?entry=gmail&source=g__;JSUrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKyslJSsrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrJSUrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysr!!Mak6IKo!KdbaCCLAD5Cq61HUQ4b5JCrg7PjBvB9hSNDyV7cu1Dz_BxVbT-BX3ViQuoDj3YUdNbSnchnKWHwuzYJmLBg$>
Madison, WI 53706-1572
<https://urldefense.com/v3/__https://www.google.com/maps/search/1513*0D*0A**mUniversity*Avenue**A0D*0A**jMadison,*WI*0D*0A**m53706-1572?entry=gmail&source=g__;JSUrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKyslJSsrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrJSUrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysr!!Mak6IKo!KdbaCCLAD5Cq61HUQ4b5JCrg7PjBvB9hSNDyV7cu1Dz_BxVbT-BX3ViQuoDj3YUdNbSnchnKWHwuzYJmLBg$>
608 772 0914 <tel:(608)%20772-0914>
http://sbel.wisc.edu/
<http://sbel.wisc.edu/>
http://projectchrono.org/
<https://urldefense.com/v3/__http://projectchrono.org/__;!!Mak6IKo!NNZn_b2z9W4LO4J581E-MjNPOiP3Ycu6Aq4Tl1QDCtM_LLuFYDaL6-RQ1C6nAeNfanFjXrRNIOIfwQNCC_e1hx3RfFuX_A$>
---------------------------------------------
*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$>
<https://urldefense.com/v3/__https://www.google.com/maps/search/1513*University*Avenue**A0D*0A**vMadison,*WI*53706-1572?entry=gmail&source=g__;KysrJSUrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKysrKys!!Mak6IKo!KdbaCCLAD5Cq61HUQ4b5JCrg7PjBvB9hSNDyV7cu1Dz_BxVbT-BX3ViQuoDj3YUdNbSnchnKWHwuAFTp9YI$>
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$>
608 772 0914 <tel:(608)%20772-0914>
http://sbel.wisc.edu/
<http://sbel.wisc.edu/>
http://projectchrono.org/
<https://urldefense.com/v3/__http:/projectchrono.org/__;!!Mak6IKo!Od8BEUkPpm5WoEens9KtQIg47iogD1i2m9LDYGHeEv2M8GiWuVl9N0Stk5HjyF-DIbSFX75lM0FtMmwz$>
---------------------------------------------
*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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