Hierarchical Reactive Control for Soccer Playing Humanoid Robots

What drives thousands of researchers worldwide to devote their creativity and energy to make robots kick a ball into a goal? The answer lies not only in the fascination of the soccer game, but rather in the quest to advance the fields of artificial intelligence research and robotics. AI researchers started to investigate games early-on. Already in the 1950th, Simon predicted that computers would be able to win against the human chess world champion within ten years (Simon & Newell , 1958). Playing chess was viewed as the epitome of intelligence. The dominant view at that time was that human intelligence could be simulated by manipulating symbols. While the chess world champion was defeated by a machine in 1997 (Newborn, 1997), human intelligence is still far from being understood. The basis for intelligent action is the perception of the world. Already this seemingly easy task frequently exceeds the capabilities of current computer systems. Perceptual processes, which interpret the flood of stimuli streaming into our senses and make it accessible for behavior control, are mostly unconscious. Hence, we are not aware of the difficulties involved. The performance of our perceptual system becomes clear only when trying to solve the same task with machines. This applies to behavior control as well. Human locomotion, for example, does not seem to be problematic. That walking and running on two legs is not an easy task becomes clear only when one tries to implement it on a real robot. Based on these observations, a view on intelligence has established itself over the last two decades that does not rely on manipulating symbols, but emphasizes the interaction of an agent with its environment (Brooks 1990; Pfeifer & Scheier 1999). The term embodiment stresses the importance of having a body as the physical basis for intelligence. Situatedness of an agent in a rich environment enables feedback from its actions to its sensory signals. The complexity of the interaction is increased significantly when the environment does not only contain passive objects, but other agents as well.