Open-R Techno Forum Japan 2003

This event was celebrated in Tokyo Japan on November 29, 2003.   My team was composed only by my wife, my two children and me.   We obtained the second best score out of 21 teams.  In the PK competition, a pink ball was located on one of the corners of a constructed soccer field.   AIBO had to search the ball and the goal locations and then score one goal.  Time employed to score the goal was measured and the team having the shortest time was considered to win the contest.     During my participation, my robot employed 18.34 seconds to score the goal.  

In order to reach the objectives, a program written in Open-R  environment was developed.   At first, the robot is searching for both, the goal and the ball locations.  As soon as finding both places, the robot is trying to calculate the environment of the ball position.  That is, if the ball is located on the corner or if the ball is located near one of the lateral white lines.   This is reached by measuring the amount of white pixels located around the ball.   In all cases, the answer behavior of the robot was scheduled to be different.   For example, if the ball is located just on the corner, the robot is scheduled to move one of its front legs in order to take out the ball from that place.  If the ball is located a little far from one of the lines, it was scheduled to take the ball with his hands and then moving its body toward the goal. 

During this step, of course, the robot was scheduled to select the most appropriate leg to hit the ball.   The left or the right leg is selected after calculating the ball and the goal positions. 

The most important part is the way of hitting the ball with its legs.  That is, if the ball is so far from the goal, the ball had to be thrown employing good power but if the ball is located near the goal, the ball must be thrown using only a small amount of power.   In order to do this, an artificial neural network was constructed.  Almost the same technique employed for the RoboCup Japan Open 2003  was used in order to know where the robot is located respect to the soccer field.   

The distances from the bottom of images to the white lines in the picture was calculated and this information was used as the input of the neural network. The goal color was defined as blue, so that, the amount of blue color on images and the center of this color was calculated by the robot and then the neural network was able to give the amount of "power" to be employed by its legs in order to make the ball to reach the goal.   After several experiments, a list of 5 different "amount of powers" was constructed and it was used for the training process.   Power 1 means almost no power and power 5 was defined to have a very big power.    Power was changed by changing the velocity on the robot legs.    

The neural network was constructed using 9 input units, 4 hidden units and 5 output units as is shown in Fig. 1. 



Figure 1.  Neural network for calculating the "amount of power".


I obtained the second best score out of 21 teams.   During my participation, my robot Aibo  was able to score one goal just 18.34 seconds after starting the competition.

The time out was setup in 2 minutes.


Videos of my participation and other teams participation can be seen here.





This site was last updated 07/06/14