Neuromorphic engineering is a growing and promising discipline nowadays. Neuro-inspiration and brain understanding applied to solve engineering problems is boosting new architectures, solutions and products today. The biological brain and neural systems process information at relatively low speeds through small components, called neurons, and it is impressive how they connect each other to construct complex architectures to solve in a quasi-instantaneous way visual and audio processing tasks, object detection and tracking, target approximation, grasping…, etc., with very low power. Neuromorphs are beginning to be very promising for a new era in the development of new sensors, processors, robots and software systems that mimic ...
Deep Learning algorithms have become one of the best approaches for pattern recognition in several f...
Emulating the sense of touch is fundamental to endow robotic systems with perception abilities. This...
Neuromorphic computing is promising to become a future standard in low-power AI applications. The in...
Linares-Barranco A, Perez-Peña F, Jimenez-Fernandez A, Chicca E. ED-BioRob: A Neuromorphic Robotic A...
Compared to classic robotics, biological nervous systems respond to stimuli in a fast and efficient ...
This paper presents a spike-based control system applied to a fixed robotic platform. Our aim is to...
Neuromorphic engineering tries to mimic biological information processing. Address-Event Representa...
This live demonstration presents an audio-guided neuromorphic robot: from a Neuromorphic Auditory S...
Morabito FC, Andreou AG, Chicca E. Neuromorphic Engineering: From Neural Systems to Brain-Like Engin...
Modelling functionalities of the brain in human-robot interaction contexts requires a real-time unde...
Neuromorphic electronic systems exhibit advantageous characteristics, in terms of low energy consump...
This paper presents an implementation of a neuro-inspired algorithm called VITE (Vector Integration...
Neuromorphic engineering takes inspiration from biology to solve engineering problems using the org...
Multisensory integration is commonly used in various robotic areas to collect more environmental i...
Autonomous robots have become a very popular topic within the artificial intelligence field. These ...
Deep Learning algorithms have become one of the best approaches for pattern recognition in several f...
Emulating the sense of touch is fundamental to endow robotic systems with perception abilities. This...
Neuromorphic computing is promising to become a future standard in low-power AI applications. The in...
Linares-Barranco A, Perez-Peña F, Jimenez-Fernandez A, Chicca E. ED-BioRob: A Neuromorphic Robotic A...
Compared to classic robotics, biological nervous systems respond to stimuli in a fast and efficient ...
This paper presents a spike-based control system applied to a fixed robotic platform. Our aim is to...
Neuromorphic engineering tries to mimic biological information processing. Address-Event Representa...
This live demonstration presents an audio-guided neuromorphic robot: from a Neuromorphic Auditory S...
Morabito FC, Andreou AG, Chicca E. Neuromorphic Engineering: From Neural Systems to Brain-Like Engin...
Modelling functionalities of the brain in human-robot interaction contexts requires a real-time unde...
Neuromorphic electronic systems exhibit advantageous characteristics, in terms of low energy consump...
This paper presents an implementation of a neuro-inspired algorithm called VITE (Vector Integration...
Neuromorphic engineering takes inspiration from biology to solve engineering problems using the org...
Multisensory integration is commonly used in various robotic areas to collect more environmental i...
Autonomous robots have become a very popular topic within the artificial intelligence field. These ...
Deep Learning algorithms have become one of the best approaches for pattern recognition in several f...
Emulating the sense of touch is fundamental to endow robotic systems with perception abilities. This...
Neuromorphic computing is promising to become a future standard in low-power AI applications. The in...