Challenge Contact: Prof. Dr. Andreas Nüchter, +49-421-200-3181, a[email protected] Approach Results Future Work References Development of a Cheap Chess Development of a Cheap Chess Robot: Planning and Perception Robot: Planning and Perception • Build a chess playing robot with as minimal constraints as possible on the game. • Allow for a non-static camera setup i.e. camera movable around during the game. • Use a standard chessboard set with no modifications. • Use off-the-shelf camera, e.g. In our case, approx 50 Euro Logitec Webcam. • Use a cheap robot arm, in our case a 4 DOF + 2- Plate Gripper arm with joints driven by AX-12 Dynamixel servos, all assembled from standard kit. • Use a standard chess engine to generate the appropriate chess moves. • Use image snapshots of the game scene at every time step and compare to determine moves made. • Use image processing to find the 4 corners of the chessboard, perpective projection, line and Canny detection [2] etc. • Pass moves to chess engine and interpret given moves into locations using chessboard size information. • Use BiRRT [1] for motion planning and compare with just computing the end effector IK at each iteration. • Add constraints into the planning like 'uprightness' of chess pieces. • Implementation using OpenCV [5], OpenRAVE [4] and ROS (Robot Operarating System) [3] • Experiments with perception showed reliable move detection with real-time perfomance comparable to previous modified chess cases. • Motion planning produced better trajectories (smoothness) compared to manual IK solving techniques. • Overall, performance in playing chess comparable to those of previous robots with modified chessboards/configurations. • Adding more links to the robot arm to have 6 DOFs which are easier to plan with. • Using a depth camera, e.g. Kinect for the move detection. [1] R. Diankov. Automated Construction of Robotic Manipulation Programs. PhD thesis, Robotics Institute, August 2010. [2] M. Sonka, V. Hlavac, and R. Boyle. Image Processing, Analysis, and Machine Vision. Thomson-Engineering, 2007. [3] http://www.ros.org/wiki [4] http://www.openrave.org [5] http://opencv.willowgarage.com/wiki/ Billy Okal and Oliver Dunkley Contact: Billy Okal, [email protected]

Development of a Cheap Chess Robot: Planning and Perceptionokal/docs/talks/gi_poster2012.pdf · Development of a Cheap Chess Robot: Planning and Perception • Build a chess playing

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Page 1: Development of a Cheap Chess Robot: Planning and Perceptionokal/docs/talks/gi_poster2012.pdf · Development of a Cheap Chess Robot: Planning and Perception • Build a chess playing

Challenge

Contact: Prof. Dr. Andreas Nüchter, +49-421-200-3181, [email protected]

Approach

Results

Future Work References

Development of a Cheap Chess Development of a Cheap Chess Robot: Planning and PerceptionRobot: Planning and Perception

• Build a chess playing robot with as minimal constraints as possible on the game.

• Allow for a non-static camera setup i.e. camera movable around during the game.

• Use a standard chessboard set with no modifications.

• Use off-the-shelf camera, e.g. In our case, approx 50 Euro Logitec Webcam.

• Use a cheap robot arm, in our case a 4 DOF + 2-Plate Gripper arm with joints driven by AX-12 Dynamixel servos, all assembled from standard kit.

• Use a standard chess engine to generate the appropriate chess moves.

• Use image snapshots of the game scene at every time step and compare to determine moves made.

• Use image processing to find the 4 corners of the chessboard, perpective projection, line and Canny detection [2] etc.

• Pass moves to chess engine and interpret given moves into locations using chessboard size information.

• Use BiRRT [1] for motion planning and compare with just computing the end effector IK at each iteration.

• Add constraints into the planning like 'uprightness' of chess pieces.

• Implementation using OpenCV [5], OpenRAVE [4] and ROS (Robot Operarating System) [3]

• Experiments with perception showed reliable move detection with real-time perfomance comparable to previous modified chess cases.

• Motion planning produced better trajectories (smoothness) compared to manual IK solving techniques.

• Overall, performance in playing chess comparable to those of previous robots with modified chessboards/configurations.

• Adding more links to the robot arm to have 6 DOFs which are easier to plan with.

• Using a depth camera, e.g. Kinect for the move detection.

[1] R. Diankov. Automated Construction of Robotic Manipulation Programs. PhD thesis, Robotics Institute, August 2010.

[2] M. Sonka, V. Hlavac, and R. Boyle. Image Processing, Analysis, and Machine Vision. Thomson-Engineering, 2007.[3] http://www.ros.org/wiki [4] http://www.openrave.org [5] http://opencv.willowgarage.com/wiki/

Billy Okal and Oliver Dunkley

Contact: Billy Okal, [email protected]

http://www.ros.org/