I'm Stéphane, a roboticist who enjoys teaching things to balance and walk. I have developed locomotion software for HRP-4 humanoids and ANYmal quadrupeds. You can read the algorithms in the corresponding publications or grab the code on GitHub. I also post technical notes to my blog. Don't hesite to send me an e-mail, answer guaranteed if you use my GPG key :-)
I've been wondering why we don't have more walking machines around us already. One explanation is that there is a scalability ceiling in implementing locomotion by control systems. For example, in the walking controller that makes the HRP-4 humanoid climb stairs, the most critical part for reliability is the robot's stabilizer, which decides how to keep balance in reaction to disturbances: roll the ankle? Shift the pelvis? Maybe tilt the torso as well? On HRP-4, all these strategies were implemented by high-frequency control systems such as linear feedback (with gain parameters) and model predictive controllers (with cost parameters), whose tuning is challenging to scale to new behaviors.
I search for methods and modalities that will allow us to go beyond the parameter tuning ceiling on real robots, especially those that are flexible and have slow brains.
I'm a strong supporter of open access and was fortunate to be able to release my research works as pre-prints and source code for all but a few exceptions. On top of open access, I see three ways in which the robotics community can improve itself: overlay journals, post-prints, and raising our standards in terms of code distribution.