3 citations · 4 across the 3 of their papers we have counts for
3 papers · 1 filter
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…
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…
PUCK: Parallel Surface and Convolution-kernel Tracking for Event-Based Cameras
Luna Gava, Marco Monforte, Massimiliano Iacono +2
Low latency and accuracy are fundamental requirements when vision is integrated in robots for high-speed interaction with targets, since they affect system reliability and stabilit…