CMUnited-97 successfully demonstrated the feasibility and effectiveness of teams of multiagent robotic systems. Within this paradigm, one of the major challenges was to ``close the loop,'' i.e., to integrate all the different modules, ranging from perception to strategic multiagent reasoning. CMUnited is an example of a fully implemented multiagent system in which the loop is closed. In addition, we implemented interesting strategic behaviors, including agent collaboration and real-time evaluation of alternative actions.
It is generally very difficult to accumulate significant scientific results to test teams of robots. Realistically, extended runs are prohibited by battery limitations and the difficulty of keeping many robots operational concurrently. Furthermore, we only had the resources to build a single team of five robots, with one spare so far. Therefore, we offer a restricted evaluation of CMUnited based on the results of four effective 10-minute games that were played at RoboCup-97. We also include anecdotal evidence of the multiagent capabilities of the CMUnited-97 robotic soccer team.
The CMUnited-97 robot team played games against robot teams from Nara Institute of Science and Technology (NAIST), Japan; University of Paris VI, France (team name ``MICROB''); and University of Girona, Spain. The results of the games are given in Table 1.
Table 1: The scores of CMUnited's games in the small robot league of
RoboCup-97. CMUnited-97 won all four games.
In total, CMUnited-97 scored thirteen goals, allowing only one against. The one goal against was scored by the CMUnited goalkeeper against itself, though under an attacking situation from France. We refined the goalkeeper's goal behavior, as presented in Section 3.2.3, following the observation of our goalkeeper's error.
As the matches proceeded, spectators noticed many of the team behaviors described in Section 3.2. The robots switched positions during the games, and there were several successful passes. The most impressive goal of the tournament was the result of a 3-way passing play: one robot passed to a second, which passed to a third, which shot the ball into the goal.
In general, the robots' behaviors were visually appealing and entertaining to the spectators. Several people attained a first-hand appreciation for the difficulty of the task as we let them try controlling a single robot with a joystick program that we developed. All of these people (several children and a few adults) found it quite difficult to maneuver a single robot well enough to direct a ball into an open goal. These people in particular were impressed with the facility with which the robots were able to pass, score, and defend.
We are aware that many issues are clearly open for further research and development. We are currently systematically identifying them and addressing them towards our next team version. In particular, we are planning on enhancing the robot's behaviors by using machine learning techniques. We are currently developing techniques to accumulate and analyze real robot data.