An Astrocyte-Modulated Neuromorphic Central Pattern Generator for Hexapod Robot Locomotion on Intel's Loihi

TL;DR

This paper introduces a neuromorphic central pattern generator based on spiking neural-astrocytic networks, enabling robust, energy-efficient hexapod robot locomotion on Intel's Loihi chip, with real-time control and noise resilience.

Contribution

It presents the first astrocyte-modulated neuromorphic CPG integrated with Loihi for robot locomotion, combining biological mechanisms with hardware implementation.

Findings

Loihi-based CPG successfully controls hexapod walking.

Robustness to sensory noise demonstrated.

Effective real-time interaction with ROS environment.

Abstract

Locomotion is a crucial challenge for legged robots that is addressed "effortlessly" by biological networks abundant in nature, named central pattern generators (CPG). The multitude of CPG network models that have so far become biomimetic robotic controllers is not applicable to the emerging neuromorphic hardware, depriving mobile robots of a robust walking mechanism that would result in inherently energy-efficient systems. Here, we propose a brain-morphic CPG controler based on a comprehensive spiking neural-astrocytic network that generates two gait patterns for a hexapod robot. Building on the recently identified astrocytic mechanisms for neuromodulation, our proposed CPG architecture is seamlessly integrated into Intel's Loihi neuromorphic chip by leveraging a real-time interaction framework between the chip and the robotic operating system (ROS) environment, that we also propose. Here, we demonstrate that a Loihi-run CPG can be used to control a walking robot with robustness to sensory noise and varying speed profiles. Our results pave the way for scaling this and other approaches towards Loihi-controlled locomotion in autonomous mobile robots.