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Intelligent Trial & Error Algorithm for Robot Adaptation
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README.md

IT&E Hexapod Experiments

Limbo experiment: IT&E code for developing hexapod experiments similar to Cully et al. (2015), Nature. This code is not replicating the exact experiments of the Nature paper, but can be seen as a more modern implementation of the underlying algorithm.

Citing this code

If you use our code for a scientific paper, please cite:

Antoine Cully, Jeff Clune, Danesh Tarapore, and Jean-Baptiste Mouret. "Robots that can adapt like animals." Nature 521, no. 7553 (2015): 503-507.

In BibTex:

@article{cully_robots_2015,
    title = {Robots that can adapt like animals},
    volume = {521},
    pages = {503--507},
    number = {7553},
    journal = {Nature},
    author = {Cully, Antoine and Clune, Jeff and Tarapore, Danesh and Mouret, Jean-Baptiste},
    year = {2015}
}

Authors

  • Author/Maintainer: Konstantinos Chatzilygeroudis
  • Other contributors: Vassilis Vassiliades, Antoine Cully, Jean-Baptiste Mouret

How to compile

Dependencies

Setting up the ResiBots environment

We use the environmental RESIBOTS_DIR variable for easy configuration and library finding (it basically points to one folder where every local installation happens that is related to the project). Thus, before installing/compiling anything, make sure that you add this line to your ~/.bashrc or ~/.zshrc file:

export RESIBOTS_DIR=/path/to/resibots/installation/folder

From now on, we assume that the RESIBOTS_DIR variable is set.

Installing DART

To simulate our hexapod we are using the DART simulator. To install use the following procedure:

sudo apt-add-repository ppa:libccd-debs/ppa
sudo apt-add-repository ppa:fcl-debs/ppa
sudo apt-add-repository ppa:dartsim/ppa
sudo apt-get update

sudo apt-get install build-essential cmake pkg-config git
sudo apt-get install libeigen3-dev libassimp-dev libccd-dev libfcl-dev libboost-regex-dev libboost-system-dev libode-dev
sudo apt-get install libopenscenegraph-dev

sudo apt-get install libtinyxml-dev libtinyxml2-dev
sudo apt-get install liburdfdom-dev liburdfdom-headers-dev

cd /path/to/tmp/folder
git clone git://github.com/dartsim/dart.git
cd dart
git checkout v6.3.0

mkdir build
cd build
cmake -DDART_ENABLE_SIMD=ON ..
make -j4
sudo make install

Installing the hexapod common files

In order to simulate the hexapod you nead to get the URDF file and the controller library:

cd /path/to/tmp/folder
git clone https://github.com/resibots/hexapod_common.git
cd hexapod_common/hexapod_models
./waf configure --prefix=$RESIBOTS_DIR
./waf install
cd ../hexapod_controller
./waf configure --prefix=$RESIBOTS_DIR
./waf
./waf install

Installing the DART wrapper

To facilitate the simulation we have created a simple wrapper over the DART simulator that is specific to our hexapod robot:

cd /path/to/tmp/folder
git clone https://github.com/resibots/hexapod_simu.git
cd hexapod_simu/hexapod_dart
./waf configure --prefix=$RESIBOTS_DIR
./waf
./waf install

Installing limbo's dependencies

sudo apt-get update
sudo apt-get install libeigen3-dev libboost-serialization-dev libboost-filesystem-dev libboost-test-dev libboost-program-options-dev libboost-thread-dev libboost-regex-dev libboost-graph-dev
sudo apt-get install libtbb-dev

Compiling the experiment

  • Get limbo: git clone https://github.com/resibots/limbo.git
  • Go to your limbo root directory
  • Create an experiment folder (if there's none) and cd to it: mkdir exp && cd exp
  • Clone ite_v2: git clone https://github.com/resibots/ite_v2.git
  • Go back to your limbo root directory
  • Configure the experiment: ./waf configure --exp ite_v2
  • Compile the experiment: ./waf --exp ite_v2

How to run

  • Compile the experiment (as shown above)
  • Run it (assuming you are on limbo root dir and the RESIBOTS_DIR folder is set properly):
    • ./build/exp/ite_v2/hexapod_simu path_to_archive [-l id_of_to_be_removed] [-n number_of_BO_iterations]
    • ./build/exp/ite_v2/hexapod_graphic path_to_archive [-l id_of_to_be_removed] [-n number_of_BO_iterations] for the graphics version
    • the ids of the legs are zero-based; i.e., they span from 0 to 5
  • Some already generated archives (to save you time) are in the archives folder. You can use map_elites_hexapod_v2 to generate new ones.

Funding

This work has been funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement number 637972 - ResiBots).

LICENSE

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