How Autonomous Material Systems Enable Embodied Intelligence

In embodied intelligence (EI), already, the gravel below a robot’s foot may change the shape of the foot–storing energy and adding stability, becoming part of the machine for milliseconds prior to release. A projectile impacting a surface may partially and reversibly imbed itself into the volume, the A chemical spray may change the macromolecular orientation of the surface, changing its optical and mechanical properties, displaying a warning to human teams and changing the trajectory of a robot away or towards the source. The key difference between Physical Intelligence (robots with AI algorithms on board) and EI is how diffuse the Input/Output system of the robot is with the environment; ultimately, an EI robot has no distinguishable interface with the environment it operates in. The key enabler for EI are material systems that operate autonomously, containing sensing, actuation, computation, and energy capabilities. This talk will describe the state of the art in EI and Autonomous Material Systems (AMS’s) and what can be done to improve the field.