Neural-Robots

Abstract

Computational neuroscience provides powerful methodologies to address one of the greatest scientific challenges of our time: understanding how the nervous system controls behavior. Models of the nervous system allow for exploring the roles of neural circuits in sensory processing, cognition, behavior generation, and motor control. However, understanding how the nervous system controls behavior is impossible without the consideration of the body it evolved to function within. Embodiment addresses this critical aspect by closing the perception-action loop through real-world physical interactions. Robotics and physics-simulators effectively help bridge this gap by providing physical embodiment to computational neural models, facilitating tangible interactions with the environment. Furthermore, biological neural circuits have evolved to develop robust solutions to challenges that closely parallel those in robotics, including motor learning, adaptation to novel settings, robust locomotion, and navigation in complex environments. Harnessing solutions refined over millions of years of evolution, thus, holds immense potential to inspire the next breakthroughs in robotics.

This workshop at IROS 2025 brings together roboticists leveraging computational neuroscience to address robotics challenges and neuroscientists using robots to study neural function. Unlike previous related events, this workshop introduces cutting-edge approaches in neuroAI, neuromorphic engineering, embodied neural computation, and bio-inspired robotics to enhance the real-world applicability and robustness of robotic systems. The workshop promotes interdisciplinary collaboration, advancing fundamental understanding in neuroscience while simultaneously fostering innovative, bio-inspired solutions to contemporary robotic challenges.

Schedule

Time	Title	Speaker
9:00	Welcome presentation	-
9:05	Dissecting Spinal Locomotor Circuit Function through Neuromechanical and Robotic Embodiment	Simon Danner (online), Drexel University
9:25	In roboto: Understanding soft-bodied neuromechanics using robotic models	Victoria Webster-Wood (online), Carnegie Mellon University
9:45	Learning from Human Dyads: Embedded Strategies for Physical Adaptation in Human–Robot Collaboration	Tadej Petric, Jožef Stefan Institute
10:05	Hierarchical Learning Framework for Humanoid Robot Control	Koji Ishihara, ATR Computational Neuroscience Laboratories
10:30	Coffee Break	-
11:00	The Age of Large Language Models: Whither Brain-Inspired Intelligence?	Yansong Chua, CNAEIT
11:20	Increasing agility of insect robots through body shape morphing	Heiko Kabutz (online), University of Colorado Boulder
11:40	Proprioception and State Encoding in Soft Robots exploiting Fluids	Nana Obayashi (online), EPFL - New York University
12:00	Using robots to understand the insect brain	Barbara Webb (online), University of Edinburgh