Book ChapterDOI
A Table Tennis Robot System Using an Industrial KUKA Robot Arm
Jonas Tebbe,Yapeng Gao,Marc Sastre-Rienietz,Andreas Zell +3 more
- pp 33-45
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TLDR
This work presents a novel table tennis robot system with high accuracy vision detection and fast robot reaction based on an industrial KUKA Agilus R900 sixx robot with 6 DOF, and tests both a curve fitting approach and an extended Kalman filter for predicting the ball’s trajectory.Abstract:
In recent years robotic table tennis has become a popular research challenge for image processing and robot control. Here we present a novel table tennis robot system with high accuracy vision detection and fast robot reaction. Our system is based on an industrial KUKA Agilus R900 sixx robot with 6 DOF. Four cameras are used for ball position detection at 150 fps. We employ a multiple-camera calibration method, and use iterative triangulation to reconstruct the 3D ball position with an accuracy of 2.0 mm. In order to detect the flying ball with higher velocities in real-time, we combine color and background thresholding. For predicting the ball’s trajectory we test both a curve fitting approach and an extended Kalman filter. Our robot is able to play rallies with a human counting up to 50 consequential strokes and has a general hitting rate of 87%.read more
Citations
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Posted Content
Robotic Table Tennis with Model-Free Reinforcement Learning
Wenbo Gao,Laura Graesser,Krzysztof Choromanski,Xingyou Song,Nevena Lazic,Pannag Raghunath Sanketi,Vikas Sindhwani,Navdeep Jaitly +7 more
TL;DR: It is shown that with appropriately tuned curriculum learning on the task and rewards, policies are capable of developing multi-modal styles, specifically forehand and backhand stroke, whilst achieving 80% return rate on a wide range of ball throws.
Proceedings ArticleDOI
i-Sim2Real: Reinforcement Learning of Robotic Policies in Tight Human-Robot Interaction Loops
Saminda Abeyruwan,Laura Graesser,David B. D'Ambrosio,Avi Singh,Anish Shankar,Alex Bewley,Deepali Jain,Krzysztof Choromanski,Pannag Raghunath Sanketi +8 more
TL;DR: The proposed method, Iterative-Sim-to-Real (i-S2R), bootstraps from a simple model of human behavior and alternates between training in simulation and deploying in the real world, and presents results on an industrial robotic arm that is able to cooperatively play table tennis with human players.
Proceedings ArticleDOI
Markerless Racket Pose Detection and Stroke Classification Based on Stereo Vision for Table Tennis Robots
Proceedings ArticleDOI
Spin Detection in Robotic Table Tennis
TL;DR: A robot that successfully copes with different spin types in a real table tennis rally against a human opponent is presented.
Posted Content
Sample-efficient Reinforcement Learning in Robotic Table Tennis
TL;DR: This paper presents a sample-efficient RL algorithm applied to the example of a table tennis robot that performs competitively both in a simulation and on the real robot in a number of challenging scenarios.
References
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Journal ArticleDOI
A flexible new technique for camera calibration
TL;DR: A flexible technique to easily calibrate a camera that only requires the camera to observe a planar pattern shown at a few (at least two) different orientations is proposed and advances 3D computer vision one more step from laboratory environments to real world use.
Proceedings Article
ROS: an open-source Robot Operating System
TL;DR: This paper discusses how ROS relates to existing robot software frameworks, and briefly overview some of the available application software which uses ROS.
Journal ArticleDOI
Least-Squares Fitting of Two 3-D Point Sets
TL;DR: An algorithm for finding the least-squares solution of R and T, which is based on the singular value decomposition (SVD) of a 3 × 3 matrix, is presented.
Book ChapterDOI
Bundle Adjustment - A Modern Synthesis
TL;DR: A survey of the theory and methods of photogrammetric bundle adjustment can be found in this article, with a focus on general robust cost functions rather than restricting attention to traditional nonlinear least squares.