Qualitative Velocity and Ball Interception

  • Frieder Stolzenburg
  • Oliver Obst
  • Jan Murray
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2479)


In many approaches for qualitative spatial reasoning, navigation of an agent in a more or less static environment is considered (e.g. in the double-cross calculus [12]). However, in general, real environment are dynamic, which means that both the agent itself and also other objects and agents in the environment may move. Thus, in order to perform spatial reasoning, not only (qualitative) distance and orientation information is needed (as e.g. in [1]), but also information about (relative) velocity of objects (see e.g. [2]). Therefore, we will introduce concepts for qualitative and relative velocity: (quick) to left, neutral, (quick) to right. We investigate the usefulness of this approach in a case study, namely ball interception of simulated soccer agents in the RoboCup [10]. We compare a numerical approach where the interception point is computed exactly, a strategy based on reinforcement learning, a method with qualitative velocities developed in this paper, and the naïve method where the agent simply goes directly to the actual ball position.


cognitive robotics multiagent systems spatial reasoning 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Frieder Stolzenburg
    • 1
  • Oliver Obst
    • 1
  • Jan Murray
    • 1
  1. 1.AI research groupUniversität Koblenz-LandauKoblenzGermany

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