Reinforcement learning environments with musculoskeletal models
Completed
200
Submissions
Submissions
125
Participants
Participants
18387
Views
Views
Completed
Reinforcement learning environments with musculoskeletal models
Time-series plot of observation and activation values from a 4m walk, then the skeleton fell out of balance at 4.46m:
Horizontal axis is the number of iterations.
5m walk, then falling out of balance at 5.5m (mass center is well ahead of both feet):
The controller returns activation values above 1.0 in my case. Clipping the activation values at 1.0 causes the skeleton to fall almost instantly, so no clipping is done by osim despite the min and max values for all muscle activations are defined as 0.0 and 1.0 in the XML body model.