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Overview of 97
For the RoboCup Physical Agent Challenge-97, we offer three specific challenges, essential not only for RoboCup but also for general mobile robotics research. These challenges will specifically deal with the real robot league, rather than RoboCup's simulator league. Challenges for soft agents will be described elsewhere. The fundamental issue for researchers who wish to build real robot systems to play a soccer game in RoboCup is how to obtain basic skills to control a ball in various kinds of situations. Typical examples are to shoot the ball into the goal, to intercept the ball from an opponent, and to pass the ball to a common side player. These skills are needed to realize cooperative behaviors with common side players and competitive ones against opponents in soccer game. Among basic skills to control the ball, we selected three challenges as the RoboCup Physical Agent Challenge-97:
- moving the ball to the specified area with no, stationary, or moving obstacles,
- catching the ball from an opponent or a common side player, and
- passing the ball between two players.
These three challenges have many variations in different kinds of situations such as passing, shooting, dribbling, receiving, and intercepting the ball with/without opponents of which defense skills varies from amateur level to professional one. Although they seem very specific ones to RoboCup, these challenges can be regarded as very general tasks in the field of mobile robotics research in a flat terrain environment. Since target reaching, obstacle avoidance, and their coordination are basic tasks in the area, a task of shooting the ball avoiding opponents that try to block the player should be ranked one of the most difficult challenge in the area. Once the robot succeeds in acquiring these skills, it can move anything to anywhere if it can do. In the other aspect, these three challenges can be regarded as a sequence of one task which guide the increase of the complexity of the internal representation according to the complexity of the environment cite{Asada96j}. In the case of visual sensing, the agent can discriminate the static environment (and self body if observed) from others by directly correlating the motor commands the agent sent and the visual information observed during the motor command executions. In other words, such things can be labeled as self body or stationary environment. While, other active agents do not have a simple and straightforward relationship with the self motions. In the early stage, they are treated as noise or disturbance because of not having direct visual correlation with the self motor commands. Later, they can be found as having more complicated and higher correlation (cooperation, competition, and others). The complexity is drastically increased. Between them there is a ball which can be stationary or moving as a result of self or other agent motions. The complexities of both the environment and the internal representation of the agent can be categorized in the cognitive issue in general, and such a issue is naturally involved in this challenge. In the following, we describe the challenges more concretely.
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