Using robots to study neuroscience

I build robots that are designed to mimic real animals, like lobsters, jellyfish and honeybees. One reason to do this is to create a robot that can behave like an animal in the wild. Animals can figure their way out of tricky and unfamiliar situations, and it would be great if our robots could do the same. Modern robots often get stuck, lost, or break down, but that doesn’t happen very often with real animals. By mimicking the real animals, we hope to improve the capabilities of our robots.

I also use the animal robots to expand our understanding of how the nervous system works. How does the lobster’s brain control leg movement when the animal is walking forward? We control a robotic lobster, RoboLobster, with a simulated nervous system based on what we think is actually going on in the real lobster. By comparing how RoboLobster and a real lobster behave under controlled environmental conditions, we can figure out what we do and don’t know about lobster nervous systems. If the lobster and robot behave differently, we know that something is wrong with our hypothesis of how the nervous system works, and we can run more biological experiments to figure out what is going on. By studying the relatively simple nervous system of a lobster, we can gain insight into the basics of how our own nervous systems work. Understanding such basic neuroscience principles may help us in the future to treat neurological problems such as strokes and traumatic brain injuries.

You can read more about why we use robots to study biology in this post by Angela, this Q&A with KatiePhd, or in this blog post I wrote. And for more info on our collaborative Robobees project, check out this article.

Related publications

Westphal, A, D Blustein , and J Ayers. 2013. A biomimetic neuronal network-based controller for guided helicopter flight. Lecture Notes in Computer Science, 8064:299-310. [journal page] [pdf]

Ayers, J, D Blustein & A Westphal. 2012. A Conserved Biomimetic Control Architecture for Walking, Swimming and Flying Robots. Lecture Notes on Artificial Intelligence, 7375, 1-12. [journal page] [pdf]

Ayers, J, A Westphal & D Blustein. 2011. A Conserved Neural Circuit-based Architecture for Ambulatory and Undulatory Biomimetic Robots. Marine Technology, 45(4):147-152. [journal page] [pdf]

Blustein, D & J Ayers. 2010. A conserved network for control of arthropod exteroceptive optical flow reflexes during locomotion. Lect Notes Artificia lntelligence, 6226:72-81. [online excerpt] [pdf]