The design of robots that interact autonomously with the environment and exhibit complex
behaviours is an open challenge that can benefit from understanding what makes living …

The rapid increase of wearable sensor devices poses new challenges for implementing
continuous real-time processing of physiological data. Neuromorphic sensory-processing …

Spiking Neuronal Networks (SNNs) realized in neuromorphic hardware lead to low-power
and low-latency neuronal computing architectures. Neuromorphic computing systems are …

Muscles are stretched with bursts of spikes that come from motor neurons connected to the
cerebellum through the spinal cord. Then, alpha motor neurons directly innervate the …

Locomotion is a crucial challenge for legged robots that is addressed “effortlessly” by
biological networks abundant in nature, named central pattern generators (CPG). The …

Neuromorphic computing is a new paradigm for design of both the computing hardware and
algorithms inspired by biological neural networks. The event-based nature and the inherent …

Neuromorphic engineering promises the deployment of low latency, adaptive and low power
systems that can lead to the design of truly autonomous artificial agents. However, many …

Evolution gave humans advanced gras** capabilities combining an adaptive hand with
efficient control. Gras** motions can quickly be adapted if the object moves or deforms …

Compared to classic robotics, biological nervous systems respond to stimuli in a fast and
efficient way regarding the body motor actions. Decision making, once the sensory …

Wearable sensor devices are disrupting healthcare technologies with a rapid increase of
systems able to perform continuous monitoring of physiological data. These systems …