Visuomotor Coordination

From collaboration with the University of Waterloo in human experiments, to understanding of the brain's perceptual and decision making apparatus, to realization of computational models in robots.

Representative Publications

Neuromorphic Computing
Robots and Animals

Neuromorphic Computing is an event based system which mimics spike based communication between neurons in the brain.

We pioneered using mutually connected spiking neurons to control real robots. We also collaborated in building spiking aVLSI circuits into a "CPG-Chip"

We have collaborated with neuroscientist mutally entrain our chip with the spinal cords of animals.

We have built circuits which can drive under-actuated, robots that feature biarticular 'muscles'

Representative Publications

Robot Learning

Learning is a key feature of intelligence.

We were the first to adapt a neural network to control a real robot in real-time 30 years ago.

We also explored how to use a collection of simple learning modules, that when sequenced could program a robot to walk. We used an abstraction of neural modules called "ring-rules" which sit between limit-cycle oscillators and decision trees.

We developed neural perceptual predictors for locomotion to extract novelty from a visual stream. This is patented work.

Representative Publications


We co-invented the "virtual structures" method of formation flying. Given a any number of robots, maintain a formation using he biological notion of heterarchical control- the antithesis of hierarchical control fist highlighted by Avis Cohen.

Applications: Large baseline space telescopes, drones in formation, manipulation of payloads using multiple drones

Behavior based control system intertwines planning, reactivity and control.

Representative Publications