We have seen plenty of robots that can jump, roll, and recover after a fall. Teaching them to jump very high comes with its own unique challenges. This video from Open Dynamic Robot Initiative shows how a quadruped learns to jump as high as possible using Bayesian optimization with unknown constraints (BOC).
The robot learns to avoid failures and what is causing them. You can find out more about it here.