Self-Learning Event Mistiming Detector Based on Central Pattern Generator

Abstract

A repetitive movement pattern of many animals, a gait, is controlled by the Central Pattern Generator (CPG), providing rhythmic control synchronous to the sensed environment. As a rhythmic signal generator, the CPG can control the motion phase of biomimetic legged robots without feedback. The CPG can also act in sensory synchronization, where it can be utilized as a sensory phase estimator. Direct use of the CPG as the estimator is not common, and there is little research done on its utilization in the phase estimation. Generally, the sensory estimation augments the sensory feedback information, and motion irregularities can reveal from comparing measurements with the estimation. In this work, we study the CPG in the context of phase irregularity detection, where the timing of sensory events is disturbed. We propose a novel self-supervised method for learning mistiming detection, where the neural detector is trained by dynamic Hebbian-like rules during the robot walking. The proposed detector is composed of three neural components: (i) the CPG providing phase estimation, (ii) Radial Basis Function neuron anticipating the sensory event, and (iii) Leaky Integrate-and-Fire neuron detecting the sensory mistiming. The detector is integrated with the CPG-based gait controller. The mistiming detection triggers two reflexes: the elevator reflex, which avoids an obstacle, and the search reflex, which grasps a missing foothold. The proposed controller is deployed and trained on a hexapod walking robot to demonstrate the mistiming detection in real locomotion. The trained system has been examined in the controlled laboratory experiment and real field deployment in the Bull Rock cave system, where the robot utilized mistiming detection to negotiate the unstructured and slippery subterranean environment.

Editorial: Biological and Robotic Inter-Limb Coordination

“…This mechanism enables the robot to effectively estimate its walking state (i.e., estimating the GRFs from joint torques) and classify terrains for adaptive locomotion. Szadkowski et al (2021) proposed a novel self-supervised method based on dynamic Hebbian-like rules for learning sensory event mistiming detection during robot walking. The sensory mistiming detector is integrated into central CPG-based control.…”

Insect-Inspired Robots: Bridging Biological and Artificial Systems

“…While Walknet control shows impressive performance for versatile and adaptive robot behavior generation (locomotion and object manipulation), it may lead to unstable robot behavior or failure in cases of sensory failure. Therefore, a combination of CPG-and reflex-based control has been actively investigated and various types of this combination have been developed [142,[197][198][199][200][201][202][203]. For instance, CPG-based control with a sensory event mistiming detection method and reflexes was proposed [201].…”

“…Therefore, a combination of CPG-and reflex-based control has been actively investigated and various types of this combination have been developed [142,[197][198][199][200][201][202][203]. For instance, CPG-based control with a sensory event mistiming detection method and reflexes was proposed [201]. The mistiming detection method consists of a CPG for estimating the sensory phase, a radial basis function (RBF) neuron for estimating the sensory event, and a leaky-integrate-and-fire neuron for detecting the sensory mistiming and activating reflexes to avoid an obstacle and search for a foothold.…”

A protocol to analyze the global literature on the clinical benefit of interlimb-coordinated intervention in gait recovery and the associated neurophysiological changes in patients with stroke

“…The rhythmic control of gait motion is primarily modulated by the central pattern generator (CPG) and the peripheral sensory feedback that provides the basic synchronous movements of the arms and legs ( 30 ). CPG is the functional network of the spinal neurons that regulates the neural coupling of the four limbs at the spinal level during rhythmic task, such as walking and stepping ( 31 ).…”