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Add FootstepNet Envs to doc project page (#2058)
* Add FootstepNet Envs to doc projects page * Update Changelog + typo * Update FootstepNet description --------- Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
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@ -39,6 +39,7 @@ Documentation:
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- Added Decisions and Dragons to resources. (@jmacglashan)
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- Updated PyBullet example, now compatible with Gymnasium
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- Added link to policies for ``policy_kwargs`` parameter (@kplers)
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- Add FootstepNet Envs to the project page (@cgaspard3333)
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- Added FRASA to the project page (@MarcDcls)
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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
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| Github: https://github.com/corentinlger/ER-MRL
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| Paper: https://arxiv.org/abs/2312.06695
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FootstepNet Envs
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----------------
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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.
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Real world experiments were conducted during RoboCup competitions on the Sigmaban robot, a small-sized humanoid designed by the *Rhoban Team*.
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| Authors: Clément Gaspard, Grégoire Passault, Mélodie Daniel, Olivier Ly
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| Github: https://github.com/Rhoban/footstepnet_envs
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| Paper: https://arxiv.org/abs/2403.12589
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FRASA: Fall Recovery And Stand up agent
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---------------------------------------
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@ -265,4 +276,4 @@ various external disturbances and stand up in a few seconds.
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Authors: Marc Duclusaud, Clément Gaspard, Grégoire Passault, Mélodie Daniel, Olivier Ly
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Github: https://github.com/Rhoban/frasa
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Paper: https://arxiv.org/abs/2410.08655
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Video: https://www.youtube.com/watch?v=NL65XW0O0mk
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Video: https://www.youtube.com/watch?v=NL65XW0O0mk
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