The robots track these predicted trajectories using reinforcement learning
kache#488
https://wholebodylocomotion.github.io/
In this work we explored how to repurpose terrain-aware human locomotion skills in a scalable and versatile way: like the action-free world model, we predict how humans will move online, and then let the humanoid track it with RL.
⛰️We try to push motion learning beyond what one can do on flat ground.
Kudos to Zewei Zhang @ctki49, Kehan Wen @KehanWen170077, and Michael Xu @mxu_cg, who made this a reality.
Check out now https://wholebodylocomotion.github.io/
https://wholebodylocomotion.github.io/
In this work we explored how to repurpose terrain-aware human locomotion skills in a scalable and versatile way: like the action-free world model, we predict how humans will move online, and then let the humanoid track it with RL.
The robots track these predicted trajectories using reinforcement learning
kache#488https://wholebodylocomotion.github.io/
In this work we explored how to repurpose terrain-aware human locomotion skills in a scalable and versatile way: like the action-free world model, we predict how humans will move online, and then let the humanoid track it with RL.
Many users praised the humanoid robot terrain navigation research using human motion predictions because they found the collaboration and joint optimization ideas cool and innovative.
