2 research outputs found
Trajectory solutions for a game-playing robot using nonprehensile manipulation methods and machine vision
The need for autonomous systems designed to play games, both strategy-based and
physical, comes from the quest to model human behaviour under tough and
competitive environments that require human skill at its best. In the last two decades,
and especially after the 1996 defeat of the world chess champion by a chess-playing
computer, physical games have been receiving greater attention. Robocup TM, i.e.
robotic football, is a well-known example, with the participation of thousands of
researchers all over the world. The robots created to play snooker/pool/billiards are
placed in this context. Snooker, as well as being a game of strategy, also requires
accurate physical manipulation skills from the player, and these two aspects qualify
snooker as a potential game for autonomous system development research. Although
research into playing strategy in snooker has made considerable progress using
various artificial intelligence methods, the physical manipulation part of the game is
not fully addressed by the robots created so far. This thesis looks at the different ball
manipulation options snooker players use, like the shots that impart spin to the ball in
order to accurately position the balls on the table, by trying to predict the ball
trajectories under the action of various dynamic phenomena, such as impacts.
A 3-degree of freedom robot, which can manipulate the snooker cue on a par with
humans, at high velocities, using a servomotor, and position the snooker cue on the
ball accurately with the help of a stepper drive, is designed and fabricated. [Continues.