By Russell L. Andersson
This journey de strength in experimental robotics paves the best way towards figuring out dynamic environments in imaginative and prescient and robotics. It describes the 1st robotic in a position to play, or even beat, human ping-pong gamers. developing a computing device to play ping-pong used to be proposed years in the past as a very tricky challenge requiring speedy, actual sensing and actuation, and the intelligence to play the sport. The learn said right here all started as a sequence of experiments in development a real real-time imaginative and prescient approach. The ping-pong desktop contains sensor and processing thoughts in addition to the thoughts had to intelligently plan the robot's reaction within the fraction of a moment to be had. it prospers on a continuing circulation of recent facts. Subjectively comparing and enhancing its movement plan because the info arrives, it presages destiny robotic platforms with many joints and sensors that needs to do an analogous, it doesn't matter what the duty. Contents: advent. robotic Ping-Pong. method layout. Real-Time imaginative and prescient approach robotic Controller. professional Controller Preliminaries. specialist Controller. robotic Ping-Pong program. end. Russell L. Andersson is Member of Technical employees, Robotics structures examine division, AT&T Bell Laboratories. A robotic Ping-Pong participant is integrated within the synthetic Intelligence sequence, edited by means of Patrick Winston and Michael Brady.
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Additional info for A Robot Ping-Pong Player: Experiments in Real-Time Intelligent Control
Each section is comprised of an initial qualitative discussion, followed by a quantitative analysis which may not be of interest to all readers. It is largely intended for those who may build their own ping-pong robots. 1 Aerodynamics. While in flight, the ping-pong ball is acted on by three significant forces: gravity, air drag, and the Magnus (spin) Effect. 86 m/sec2 (referred to as I G ) . The aerodynamic forces acting upon a smooth rotating sphere are surprisingly still a matter of debate among physicists.
These quantities may be used directly to pick up an object or to guide further visual processing. Second and higher-order moments may be combined to form invariants which are used to characterize an object; the invariants can discriminate among members of a set of objects. The time required to compute gray-scale moments has hindered their use. 5 seconds. Straightforward hardware implementations of moment calculations require large numbers of multipliers, accumulators, registers, and supporting logic.
The flow of data through the system begins at the twin vision processors, eyeO and eye 1. Each processor contains two real-time vision systems constituting a stereo pair. 3 msec vertical retrace interval, requiring the operating system to respond rapidly. Both 28 Chapter 3 R R SP Chief 2000 KID TL TR 1 JI-3 Striker DL DR J4-6 6 Figure 6. System Block Diagram. ) feed the vision processors, trajectory analyzer, eyeO and eye1. XYZT data is sent to the tranal, which produces predictions of the ball's path for the expert controller processor, striker.