Spin Detection in Robotic Table Tennis
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. To develop a robot that can compete with a human player, the robot needs to detect spin, so it can plan an appropriate return stroke. In this paper we compare three methods to estimate spin. The first two approaches use a high-speed camera that captures the ball in flight at a frame rate of 380 Hz. This camera allows the movement of the circular brand logo printed on the ball to be seen. The first approach uses background difference to determine the position of the logo. In a second alternative, we train a CNN to predict the orientation of the logo. The third method evaluates the trajectory of the ball and derives the rotation from the effect of the Magnus force. This method gives the highest accuracy and is used for a demonstration. Our robot successfully copes with different spin types in a real table tennis rally against a human opponent.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
A multi-modal table tennis robot system
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 accuracy vision detection and fast robot re…
Ace! Motion Planning of Professional-Level Table Tennis Serves with a Robot Arm
Table tennis, a dynamic, compact, and popular sport, has received significant attention as a robotics benchmark over the last decades. Most of the research has focused on the rally aspect - returning an incoming ball - r…
Motion PlanningAn Event-Based Perception Pipeline for a Table Tennis Robot
Table tennis robots gained traction over the last years and have become a popular research challenge for control and perception algorithms. Fast and accurate ball detection is crucial for enabling a robotic arm to rally …
Sample-efficient Reinforcement Learning in Robotic Table Tennis
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 episodes from which the agent can learn. I…
reinforcement-learningReinforcement LearningReinforcement Learning (RL)SpinDOE: A ball spin estimation method for table tennis robot
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 velocity and the magnitude of the spin values.…