Bio-inspired sensing and control of soft slithering bodies in 3D environments

We present a bio-inspired neural architecture for learning closed-loop controls in slithering soft bodies, realized through coupled oscillators and reinforcement learning. We deploy this architecture in a soft snake model and demonstrate how the snake can filter and leverage noisy sensory measurements to navigate realistic 3D environments.