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Reset-free Trial-and-Error Learning for Robot Damage Recovery

Konstantinos Chatzilygeroudis, Vassilis Vassiliades and Jean-Baptiste Mouret

Affiliations:

• Inria Nancy Grand-Est, France
• CNRS, France
• University of Lorraine, France

Citing this code

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

Chatzilygeroudis, K., Vassiliades, V., & Mouret, J.-B. (2018). Reset-free Trial-and-Error Learning for Robot Damage Recovery. Robotics and Autonomous Systems.

In BibTex:

@article{chatzilygeroudis2018resetfree,
  title = {{Reset-free Trial-and-Error Learning for Robot Damage Recovery}},
  journal = {Robotics and Autonomous Systems},
  year = {2018},
  volume = {100},
  pages = {236 - 250},
  issn = {0921-8890},
  doi = {https://doi.org/10.1016/j.robot.2017.11.010},
  url = {https://www.sciencedirect.com/science/article/pii/S0921889017302440},
  author = {Chatzilygeroudis, Konstantinos and Vassiliades, Vassilis and Mouret, Jean-Baptiste},
  organization={Elsevier}
}

Dependencies

• Ubuntu 14.04, 15.04 (and it should run on 16.04)
• DART simulator, http://dartsim.github.io/ (release-6.1 branch)
• Eigen 3, http://eigen.tuxfamily.org/
• Boost
• ROS (Optional - only for the physical robot)

Components (in alphabetical order)

General

• mcts contains the implementation of a generic and lightweight C++14 library for Monte Carlo Tree Search algorithms

Hexapod Experiments (in rte-hexa folder)

• hexapod_common contains code for the low-level controller of the hexapod (both in simulation and real robot) and a URDF model of the hexapod needed for ROS/DART.
• hexapod_ros contains code for controlling our custom physical hexapod
• hexapod_simu contains a DART integration for our hexapod [requires hexapod_common]
• limbo contains the limbo workspace for Reset-free Trial-and-Error algorithm. The actual code is in folder limbo/exp/rte-hexa/
• sferes contains the sferes workspace for generating an action repertoire with the MAP-Elites algorithm. The actual code is in folder sferes/exp/map_elites_hexapod/

Mobile Robot Experiments (in rte-mobile folder)

• libfastsim contains code for simulating simple velocity controlled differential drive robots.
• limbo contains the limbo workspace for Reset-free Trial-and-Error algorithm. The actual code is in folder limbo/exp/rte_mobile/
• sferes contains the sferes workspace for generating an action repertoire with the MAP-Elites algorithm. The actual code is in folder sferes/exp/map_elites_mobile/

Installing

Hexapod Experiments

• Install dependencies
  • export RESIBOTS_DIR=/path/to/workspace
  • cd path/to/hexapod_common/hexapod_models
  • ./waf configure --prefix=$RESIBOTS_DIR
  • ./waf install
  • cd path/to/hexapod_common/hexapod_controller
  • ./waf configure --prefix=$RESIBOTS_DIR
  • ./waf install
  • cd path/to/hexapod_simu/hexapod_dart/
  • ./waf configure --prefix=$RESIBOTS_DIR
  • ./waf install
  • cd path/to/mcts
  • ./waf configure --prefix=$RESIBOTS_DIR
  • ./waf install

Mobile Robot Experiments

• Install dependencies
  • export RESIBOTS_DIR=/path/to/workspace
  • cd path/to/libfastsim
  • ./waf configure --prefix=$RESIBOTS_DIR
  • ./waf install
  • cd path/to/mcts
  • ./waf configure --prefix=$RESIBOTS_DIR
  • ./waf install

Compiling MAP-Elites to generate the Action Repertoire

• cd path/to/sferes (rte_hexa/sferes for the hexapod and rte_mobile/sferes for the mobile robot)
• ./waf configure --exp name_of_experiment
• ./waf --exp name_of_experiment
• name_of_experiment can be either map_elites_hexapod or map_elites_mobile

Running MAP-Elites to generate Action Repertoire

Hexapod Experiments

• cd path/to/sferes (rte_hexa/sferes for the hexapod)
• ./build/exp/map_elites_hexapod/hexa_position_text_position_only
• This will generate an action repertoire in path/to/sferes/build/exp/map_elites_hexapod folder (*.bin files). Typical runs take 1-2 days in a cluster.

Mobile Robot Experiments

• cd path/to/sferes (rte_mobile/sferes for the mobile robot)
• ./build/exp/map_elites_mobile/mobile_text
• This will generate an action repertoire in path/to/sferes/build/exp/map_elites_mobile folder (*.bin files). Typical runs take a few hours in a cluster.

Compiling Reset-free Trial-and-Error learning algorithm

• cd path/to/limbo
• ./waf configure --exp name_of_experiment
• ./waf --exp name_of_experiment
• name_of_experiment can be either rte-hexa or rte_mobile
• If you have the physical hexapod append -- robot to both commands (requires ROS packages, e.g. hexapod_ros and tf)

Running Reset-free Trial-and-Error learning algorithm

Hexapod Experiments

• cd path/to/limbo (rte_hexa/limbo for the hexapod)
• ./build/exp/rte-hexa/rte_hexa_graphic_low_dim -m path/to/action_repertoire.bin -l exp/rte-hexa/test_maps/map_{0,1,2,3}.txt -i 5000 -k 0.0 -d 0.03 -p 4 -c 150 -r [list of leg indices to remove] -s [list of leg indices to shorten]
• We provide 2 sample action repertoires (action_repertoire_1.bin, action_repertoire_2.bin in path/to/limbo folder)

Mobile Robot Experiments

• cd path/to/limbo (rte_mobile/limbo for the mobile robot)
• ./build/exp/rte_mobile/rte_mobile_graphic -m path/to/action_repertoire.bin -l exp/rte_mobile/map_small.txt -p 4 -c 150 -a 0.5 -b 0.6 -i 5000 -v 30 -d 1
• We provide the action repertoires (action_repertoire.bin in path/to/limbo folder)

Notes

This version of code does not include the rough terrain experiments and the TEXPLORE baseline for the hexapod robot. Do not hesitate to contact the authors for details and/or this missing code.

Contact

Please contact Konstantinos Chatzilygeroudis (konstantinos.chatzilygeroudis@inria.fr) for any inquires or difficulties.