3 papers
cs.RO2026
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…
eess.SY2025
Benchmarking Spiking Neurons for Linear Quadratic Regulator Control of Multi-linked Pole on a Cart: from Single Neuron to Ensemble
Shreyan Banerjee, Luna Gava, Aasifa Rounak +1
The emerging field of neuromorphic computing for edge control applications poses the need to quantitatively estimate and limit the number of spiking neurons, to reduce network comp…
cs.RO2025
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…