roboschool | source software for robot simulation | Robotics library

by openai Python Version: 1.0.49 License: Non-SPDX

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | roboschool Summary

roboschool is a Python library typically used in Automation, Robotics applications. roboschool has no bugs, it has no vulnerabilities, it has build file available and it has medium support. However roboschool has a Non-SPDX License. You can install using 'pip install roboschool' or download it from GitHub, PyPI.

Release blog post is here:.

Support

Quality

Security

License

Reuse

Support

roboschool has a medium active ecosystem.

It has 2062 star(s) with 486 fork(s). There are 261 watchers for this library.

It had no major release in the last 12 months.

There are 74 open issues and 109 have been closed. On average issues are closed in 27 days. There are 8 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of roboschool is 1.0.49

Quality

roboschool has 0 bugs and 0 code smells.

Security

roboschool has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

roboschool code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

roboschool has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

roboschool releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

roboschool saves you 3112 person hours of effort in developing the same functionality from scratch.

It has 6701 lines of code, 242 functions and 54 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed roboschool and discovered the below as its top functions. This is intended to give you an instant insight into roboschool implemented functionality, and help decide if they suit your requirements.

Test function for triangulation
Push a vector onto the stack
Push a single value onto the stack
Push VT to TV
Perform a step
Calculate the state of the robot
Apply an action to the motors
Perform a step
Runs the game
Example testing example
Actual activation function
Performs a step
Performs a step
Test the game
Reset robot specific attributes
Test the convex hull
Reset robot specific attributes
Reset the game
Test the contour
Set plate parameters
Reset the robot
Calculate global step
Resets the robot
Generate an alive cage
Restart an episode
Tomographic parameters
Serve forever

Get all kandi verified functions for this library.

roboschool Key Features

No Key Features are available at this moment for roboschool.

roboschool Examples and Code Snippets

Training MULTIPOLAR in other environments

Jupyter Notebook

Lines of Code : 60

License : Non-SPDX (NOASSERTION)

Copy

python random_env_dynamic_train_cmd_gen.py --num-samples 100 --algo ppo2 --seed 0 --env RoboschoolHopper-v1 \
--params-ranges leg_length,0.35,0.65 foot_length,0.29,0.49 thigh_length,0.35,0.55 torso_length,0.3,0.5 size,0.7,1.1 damping,0.5,4 friction,0

Application of Neural Ordinary Differential Equations for Continuous Control Reinforcement Learning,Install and Run

Python

Lines of Code : 17

License : Permissive (MIT)

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git clone --recursive https://github.com/MichaelKonobeev/neuralode-rl.git
cd neuralode-rl
pip install -r requirements.txt

pip install roboschool==1.0.48

python run-mujoco.py --env-id HalfCheetah-v3 --logdir logdir/mlp/half-cheetah.00
# OR
python ru

3. Using the ,1. Introduction

Python

Lines of Code : 16

License : No License

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from RL import Trainer

model = Trainer('ENV_NAME').create_model() # ENV_NAME -> the name of the class of your environment
model.train()                              # Train the model as specified in the configuration file and save it in a unique

Community Discussions

Trending Discussions on roboschool

ImportError: cannot import name 'cpp_household' from 'roboschool'

QUESTION

ImportError: cannot import name 'cpp_household' from 'roboschool'

Asked 2020-Jun-13 at 09:03

pls help me. I can not import lib

roboschool 1.0.49 gym==0.15.4

input

...

ANSWER

Answered 2020-Jun-13 at 09:03

It looks like you're on Windows. As mentioned here, roboschool doesn't work on Windows, unfortunately.

Source https://stackoverflow.com/questions/62354041

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install roboschool

If you are running Ubuntu or Debian Linux, or OS X, the easiest path to install roboschool is via pip (:. Note: in a headless machine (e.g. docker container) you may need to install graphics libraries; this can be achieved via apt-get install libgl1-mesa-dev. If you are running some other Linux/Unix distro, or want the latest and the greatest code, or want to tweak the compiler optimization options, read on….
The compiler options are configured in the [Makefile](roboschool/cpp-household/Makefile). Feel free to tinker with them or leave those as is. To compile the project code, and then install it as a python package, use the following:.

Support

A lot of the issues during installation from source are due to missing / incorrect PKG_CONFIG_PATH variable. If the command pkg-config --cflags Qt5OpenGL assimp bullet shows an error, you can try manually finding missing *.pc files (for instance, for if the pkg-config complains about assimp, run find / -name "assimp.pc" - this is a bit bruteforce, but it works :)) and then adding folder with that files to PKG_CONFIG_PATH. Sometime distros of linux may complain about generated code being not platform-independent, and ask you to recompile something with -fPIC option (this was seen on older versions of CentOS). In that case, try removing -march=native compilation option in the Makefile. On the systems with nvidia drivers present, roboschool sometimes is not be able to find hardware-accelerated libraries. If you see errors like.

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