Overarching research goal

Robotics has come a long way since first industry applications in 1980’s. Symbolic AI and computing power have made phenomenal advances that professional services can obtain computer advice based on millions of documents. Yet, things begin to fall apart when it comes to physical contact. Despite all advances in AI, control theory, sensing and actuation, we cannot trust a robot to hold a live hamster without hurting it. We cannot trust a robot to physically examine a patient in an epidemic like Ebola. Most advanced robots find it hard to walk on an uncalibrated outdoor terrain.

It looks like we are missing a few fundamental things to do with realtime computation that living beings take for granted to survive in complex natural environments with noisy sensors and slow communication fibers in neural circuits.

We observe that the brain sometimes withdraws from direct closed loop control between sensed states and actions to an indirect mode of involvement where it conditions the body to manage challenging dynamic contact tasks. A bicycle rider would stand up with bent knees when riding on a bumpy terrain. If someone is asked to estimate the weight of an object, they would bob it up and down several times before concluding an estimate. In soft tissue palpation for instance, when a Physician is required to estimate the location of the edge of the liver of a patient using manual palpation, they would regulate the stiffness and configuration of the fingers to condition haptic perception during palpation. Therefore, the brain is smart enough to condition the body to make it efficient to solve a dynamic problem.

In the Morph Lab, we try to understand the principles behind such realtime conditioning of the physical body to improve both perception and action. Since it is difficult to unentangle parallel pathways of motor commands in a living being, we take a soft robotics approach to test questions to do with embodied intelligence. We enjoy this approach because it not only allows us to understand principles that are applicable to biological beings but also helps us to build useful soft robots.

Morphlab ICL Youtube channel

IEEE Soft Robotics Podcast:

First IEEE Soft Robotics debate on Morphological Computation and Control:

Dyson School of Design Engineering