learning_quadrupedal_locomotion_over_challenging_terrain_supplementary's Introduction

Supplementary materials for "Learning Quadrupedal Locomotion over Challenging Terrain"

Project page: https://leggedrobotics.github.io/rl-blindloco

Author: Joonho Lee ([email protected])

This repo contains

trained policy networks for ANYmal c010 and c100 models.
- c010 model is not trained with Slippery Hills terrain.
- c100 is the latest model (added during the revision)
ANYmal environments implemented in Raisim simulator.
- Height map terrain is included
- In the visualizer, press 'c' key to sample new command
- In the visualizer, press space key to re-initialize the robot

Dependencies

raisim (https://github.com/raisimTech/raisimlib)
raisimOgre (https://github.com/raisimTech/raisimOgre)
tensorflow-cpp (https://github.com/leggedrobotics/tensorflow-cpp)

Third-party

anymal_c_simple_description(https://github.com/ANYbotics/anymal_c_simple_description)

Notes

Some paths are hard-coded in test_c010.cpp and test_c100.cpp. Be caureful about them.
This repository is not maintained anymore. If you have a question, send an email to [email protected].
We don't take questions regarding installation. If you install the dependencies successfully, you can easily run this.
For the codes in rsc/robot/, ANYbotics' license is applied. MIT license otherwise.
Install the dependencies in you local build directory and link as follows.

cmake -DCMAKE_INSTALL_PREFIX=${YOUR_LOCAL_BUILD_DIRECTORY} -DCMAKE_BUILD_TYPE=Release ..

You can install tensorflow-cpp locally as follows.

cd tensorflow/tensorflow
mkdir build && cd build
cmake -DCMAKE_INSTALL_PREFIX=${YOUR_LOCAL_BUILD_DIRECTORY} -DCMAKE_BUILD_TYPE=Release ..
make install -j

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