Event cameras (EC) represent a paradigm shift and are emerging as valuable tools in the
automotive industry, particularly for in-cabin and out-of-cabin monitoring. These cameras …

Today's autonomous drones have reaction times of tens of milliseconds, which is not
enough for navigating fast in complex dynamic environments. To safely avoid fast moving …

In recent years, unmanned aerial vehicles (UAVs) have been confirmed as a powerful tool
for countless applications in nearly every industry, in which collision avoidance plays a vital …

Event-based cameras have been designed for scene motion perception-their high temporal
resolution and spatial data sparsity converts the scene into a volume of boundary …

Fusion of X-band Doppler radar and infrared sensors can offer a great advantage for close
proximity time-to-collision (TTC) prediction in the field of autonomous robot navigation due to …

The nervous systems converts the physical quantities sensed by its primary receptors into
trains of events that are then processed in the brain. The unmatched efficiency in information …

Dynamic Field Theory (DFT) is an established framework for modeling embodied cognition.
In DFT, elementary cognitive functions such as memory formation, formation of grounded …

Predicting a potential collision with leading vehicles is an essential functionality of any
autonomous/assisted driving system. One bottleneck of existing vision-based solutions is …

Recovering the camera motion and scene geometry from visual data is a fundamental
problem in computer vision. Its success in conventional (frame-based) vision is attributed to …

Learning to adapt one's gait with environmental changes plays an essential role in the
locomotion of legged robots which remains challenging for constrained computing …