Add FootstepNet Envs to doc project page (#2058)

* Add FootstepNet Envs to doc projects page

* Update Changelog + typo

* Update FootstepNet description

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Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
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cgaspard3333 2024-12-17 16:47:19 +01:00 committed by GitHub
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@ -39,6 +39,7 @@ Documentation:
- Added Decisions and Dragons to resources. (@jmacglashan)
- Updated PyBullet example, now compatible with Gymnasium
- Added link to policies for ``policy_kwargs`` parameter (@kplers)
- Add FootstepNet Envs to the project page (@cgaspard3333)
- Added FRASA to the project page (@MarcDcls)
Release 2.4.0 (2024-11-18)

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@ -251,6 +251,17 @@ It enables solving environments involving partial observability or locomotion (e
| Github: https://github.com/corentinlger/ER-MRL
| Paper: https://arxiv.org/abs/2312.06695
FootstepNet Envs
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These environments are dedicated to train efficient agents that can plan and forecast bipedal robot footsteps in order to go to a target location possibly avoiding obstacles. They are designed to be used with Reinforcement Learning (RL) algorithms.
Real world experiments were conducted during RoboCup competitions on the Sigmaban robot, a small-sized humanoid designed by the *Rhoban Team*.
| Authors: Clément Gaspard, Grégoire Passault, Mélodie Daniel, Olivier Ly
| Github: https://github.com/Rhoban/footstepnet_envs
| Paper: https://arxiv.org/abs/2403.12589
FRASA: Fall Recovery And Stand up agent
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@ -265,4 +276,4 @@ various external disturbances and stand up in a few seconds.
Authors: Marc Duclusaud, Clément Gaspard, Grégoire Passault, Mélodie Daniel, Olivier Ly
Github: https://github.com/Rhoban/frasa
Paper: https://arxiv.org/abs/2410.08655
Video: https://www.youtube.com/watch?v=NL65XW0O0mk
Video: https://www.youtube.com/watch?v=NL65XW0O0mk