31 citations · 70 across the 8 of their papers we have counts for
6 papers · 1 filter
Detection of Fast-Moving Objects with Neuromorphic Hardware
Andreas Ziegler, Karl Vetter, Thomas Gossard +3
Neuromorphic Computing (NC) and Spiking Neural Networks (SNNs) in particular are often viewed as the next generation of Neural Networks (NNs). NC is a novel bio-inspired paradigm f…
A multi-modal table tennis robot system
Andreas Ziegler, Thomas Gossard, Karl Vetter +2
In recent years, robotic table tennis has become a popular research challenge for perception and robot control. Here, we present an improved table tennis robot system with high acc…
eWand: A calibration framework for wide baseline frame-based and event-based camera systems
Thomas Gossard, Andreas Ziegler, Levin Kolmar +2
Accurate calibration is crucial for using multiple cameras to triangulate the position of objects precisely. However, it is also a time-consuming process that needs to be repeated…
Real-time event simulation with frame-based cameras
Andreas Ziegler, Daniel Teigland, Jonas Tebbe +2
Event cameras are becoming increasingly popular in robotics and computer vision due to their beneficial properties, e.g., high temporal resolution, high bandwidth, almost no motion…
Optimal Stroke Learning with Policy Gradient Approach for Robotic Table Tennis
Yapeng Gao, Jonas Tebbe, Andreas Zell
Learning to play table tennis is a challenging task for robots, as a wide variety of strokes required. Recent advances have shown that deep Reinforcement Learning (RL) is able to s…
Sample-efficient Reinforcement Learning in Robotic Table Tennis
Jonas Tebbe, Lukas Krauch, Yapeng Gao +1
Reinforcement learning (RL) has achieved some impressive recent successes in various computer games and simulations. Most of these successes are based on having large numbers of ep…