pinocchio VS lipm_walking_controller

Open-loop walking + physics: (e.g. ZMP-based) one thing you can do (that does not imply adding an IMU to Kayra and going for feedback) is include some walking physics into your walking trajectory generation. To give you an idea, I've written a tutorial on doing that in Python a couple of years ago. The libraries in this tutorial are deprecated now, but I'm working on an equivalent stack at github.com/tasts-robots using more durable software like pinocchio. The libs are still WIP but if you are interested in exploring that dev path (i.e. making a ZMP-based trajectory generator for Kayra) I can support you and help adapt them (because I want that SW to be useful for a maximum number of people).

Drake and Pinocchio both use the Python interface to Meshcat as an option for visualizing robots, and they can both do the forward kinematics and have visualizer components that place the visual meshes properly relative to the computed frames, but both of those are full-fledged and complex kinematics and dynamics libraries for contact-rich interaction (and more), so the API calls to get a model set up are doing a lot more than providing a visual model you can feed joint angles to.

Pinocchio sounds like exactly what you need: https://github.com/stack-of-tasks/pinocchio

On a related note, a ZMP-based trajectory optimizer also has a fitness function. Unfortunately it's not obvious at all in the tutorial I mentioned, there it only appears as wxt=1., wu=0.01; it's more obvious in the code and GUI of the lipm_walking_controller, where the cost function appears in the Walking → MPC tab. You can run this thing in a Docker if you want to check it out: