activity
20192024
most citedSpin Detection in Robotic Table Tennis

31 citations · 70 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2024

Table tennis ball spin estimation with an event camera

Thomas Gossard, Julian Krismer, Andreas Ziegler +2

Spin plays a pivotal role in ball-based sports. Estimating spin becomes a key skill due to its impact on the ball's trajectory and bouncing behavior. Spin cannot be observed direct…

cs.RO2024

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…

cs.RO2023★ 1 cited

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…

cs.RO2023★ 1 cited

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…

cs.CV2023★ 16 cited

SpinDOE: A ball spin estimation method for table tennis robot

Thomas Gossard, Jonas Tebbe, Andreas Ziegler +1

Spin plays a considerable role in table tennis, making a shot's trajectory harder to read and predict. However, the spin is challenging to measure because of the ball's high veloci…

cs.RO2022

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…

cs.RO2021★ 21 cited

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…

cs.RO2020

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…

cs.CV2019★ 31 cited

Spin Detection in Robotic Table Tennis

Jonas Tebbe, Lukas Klamt, Yapeng Gao +1

In table tennis, the rotation (spin) of the ball plays a crucial role. A table tennis match will feature a variety of strokes. Each generates different amounts and types of spin. T…