Oscillatory neural networks for robotic yo-yo control.

Different networks of coupled oscillators were developed for open-loop control of periodic motion. However, some tasks, like yo-yo playing, are open-loop unstable and require proper phase locking to stabilize. Given the phase-locking property of coupled oscillators, we investigate their application to closed-loop control of open-loop unstable systems, concentrating on the challenging task of yo-yo control. In particular, we focus on pulse-coupling, where the yo-yo sends a feedback upon reaching the bottom of the string and the onset of the oscillatory cycle is used to trigger the movement. Four networks involving either a stand-alone or a circuit level oscillator with either excitatory or inhibitory couplings are considered. Working curve analysis indicates that three of the networks cannot stabilize the yo-yo. The fourth network, which is based on a circuit-level oscillator, is analyzed using the return map and the region of stability is determined and verified by simulations. The resulting pulse-coupled oscillatory control provides a model-free control strategy that operates with an easy-to-measure low-rate feedback.