Central pattern generators evolved for real-time adaptation to rhythmic stimuli

Abstract

For a robot to be both autonomous and collaborative requires the ability to adapt its movement to a variety of external stimuli, whether these come from humans or other robots. Typically, legged robots have oscillation periods explicitly defined as a control parameter, limiting the adaptability of walking gaits. Here we demonstrate a virtual quadruped robot employing a bio-inspired central pattern generator (CPG) that can spontaneously synchronize its movement to a range of rhythmic stimuli. Multi-objective evolutionary algorithms were used to optimize the variation of movement speed and direction as a function of the brain stem drive and the center of mass control respectively. This was followed by optimization of an additional layer of neurons that filters fluctuating inputs. As a result, a range of CPGs were able to adjust their gait pattern and/or frequency to match the input period. We show how this can be used to facilitate coordinated movement despite differences in morphology, as well as to learn new movement patterns.

From real-time adaptation to social learning in robot ecosystems

“…We begin with the same modular CPG and recurrent filter design as in Szorkovszky et al (2023a) . Each limb module contains three Matsuoka neurons modified to have input-dependent frequency.…”

“…We used two virtual robot body layouts, simulated in Unity using the ML agents package ( Grimminger et al, 2020 ). The first body type is a short-legged quadruped, based on the Open Dynamic quadruped ( Juliani et al, 2018 ), and previously studied in Szorkovszky et al (2023a) . For this body, each motor neuron drives one joint angle (see Supplementary Material ).…”

“…The multi-objective evolutionary algorithm NSGA-III ( Deb and Jain, 2013 ) was used to simultaneously optimize CPGs for flexibility in speed and direction, as well as stability, resulting in a diverse range of CPGs spanning the Pareto front. The genotype included CPG parameters, interconnection weights and tilt feedback weights [with the same ranges as in Szorkovszky et al (2023a) for both morphologies] as well as central joint angles, angle limits and joint amplitude coefficients (see Supplementary Material of this paper for ranges).…”

“…It has recently been demonstrated that self-organization of a locomotion CPG without feedback is sufficient for real-time entrainment to external rhythms, such as those transmitted through audio ( Szorkovszky et al, 2023a ). This can be seen as an embodied version of the “dynamic attending” approach to beat perception, which was proposed using abstracted nonlinear oscillators ( Large and Jones, 1999 ).…”

“…We will first review current and potential generative approaches to social sensorimotor learning, and then demonstrate a scheme to achieve this in a diverse population of central pattern generator (CPG) based robots. The first ingredient of this process, CPGs with the ability to spontaneously entrain to periodic stimuli, has recently been achieved ( Szorkovszky et al, 2023a ). We will first demonstrate that Hebbian-like spike timing-dependent plasticity can be used to lock-in movement patterns achieved through synchronization.…”