Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead
of capturing images at a fixed rate, they asynchronously measure per-pixel brightness …

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 …

Neuromorphic hardware enables fast and power-efficient neural network–based artificial
intelligence that is well suited to solving robotic tasks. Neuromorphic algorithms can be …

Animals have evolved mechanisms to travel safely and efficiently within different habitats.
On a journey in dense terrains animals avoid collisions and cross narrow passages while …

Real-world sensory-processing applications require compact, low-latency, and low-power
computing systems. Enabled by their in-memory event-driven computing abilities, hybrid …

Motion deblurring in dynamic scenes is a challenging task when the blurring is caused by
one or a combination of various reasons such as moving objects, camera movement, etc …

Depth estimation is an important task in many robotic applications. It is necessary to
understand and navigate an environment and to interact with objects. Different active and …

Attentional selectivity tends to follow events considered as interesting stimuli. Indeed, the
motion of visual stimuli present in the environment attract our attention and allow us to react …

Unmanned aerial vehicles (UAVs) are at the forefront of this century's technological shift,
becoming ubiquitous in research and market areas. However, as a UAV navigates …