In this talk, we discuss some hardware and software practices to foster cross-lab developments in robotics. On the hardware side, we highlight the alternative made possible by recent innovations in actuators: building lighter robots of the kind that can (1) be made at home/with minimal equipment, and (2) bump, fall on, or be lifted by us with no harm. We'll discuss the example of Upkie as one instance of this template.
On the motion control side, we look at how the physics of a task dictate how fast a controller should run to perform it. Balancing, in particular, is a rather low-frequency task: it was demonstrated (in theory and on real hardware) that a DCM-based controller can balance an adult-size humanoid while running at only 10 Hz. Jumping on this, we discuss how this property allows us to write more control-critical code in a high-level language like Python. We illustrate our points with practical sub-modules from two controllers: the LIPM walking controller for HRP humanoids, implemented with mc_rtc, and the Pink controller for the Upkie wheeled-biped, implemented with Vulp (🦊).
|Recording of the presentation|
|Python code from the slides|
|Motion control software for the Upkie wheeled biped|
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