5 papers
Neuromorphic Object Detection: An In-Depth Study and Future Directions
Jianing Li, Dianze Li, Arren Glover +5
Conventional frame-based cameras face significant challenges in detecting objects under high-speed motion blur or in low-light environments. Neuromorphic cameras provide asynchrono…
NeuroAI and Beyond: Bridging Between Advances in Neuroscience and ArtificialIntelligence
Anthony Zador, Jean-Marc Fellous, Terrence Sejnowski +28
Neuroscience and Artificial Intelligence (AI) have made impressive progress in recent years but remain only loosely interconnected. Based on a workshop convened by the National Sci…
Training slow silicon neurons to control extremely fast robots with spiking reinforcement learning
Irene Ambrosini, Ingo Blakowski, Dmitrii Zendrikov +5
Air hockey demands split-second decisions at high puck velocities, a challenge we address with a compact network of spiking neurons running on a mixed-signal analog/digital neuromo…
6-DoF Object Tracking with Event-based Optical Flow and Frames
Zhichao Li, Arren Glover, Chiara Bartolozzi +1
Tracking the position and orientation of objects in space (i.e., in 6-DoF) in real time is a fundamental problem in robotics for environment interaction. It becomes more challengin…
IMA-Catcher: An IMpact-Aware Nonprehensile Catching Framework based on Combined Optimization and Learning
Francesco Tassi, Jianzhuang Zhao, Gustavo J. G. Lahr +5
Robotic catching of flying objects typically generates high impact forces that might lead to task failure and potential hardware damages. This is accentuated when the object mass t…