Abstract
This paper discusses the hierarchical control architecture used to generate the behavior of individual agents and a team of robots for the RoboCup Small Size competition. Our reactive approach is based on control layers organized in a temporal hierarchy. Fast and simple behaviors reside on the bottom of the hierar- chy, while an increasing number of slower and more complex behaviors are implemented in the higher levels. In our architecture deliberation is not implemented explicitly, but to an external viewer it seems to be present.
Each layer is composed of three modules. First, the sensor module, where the perceptual dynamics aggregates the readings of fast changing sensors in time to form complex, slow changing percepts. Next, the activation module computes the activation dynamics that determines whether or not a behavior is allowed to influence actuators, and finally the actuator module, where the active behaviors influence the actuators to match a target dynamics.
We illustrate our approach by describing the bottom-up design of behaviors for the RoboCup domain.
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References
P. Ackers, S. Behnke, B. Frötschl, W. Lindstrot, M. de Melo, R. Rojas, A. Schebesch, M. Simon, M. Sprengel, and O. Tenchio. The soul of a new machine. Technical Report B-12/99, Freie Universität Berlin, 1999.
M. Asada and H. Kitano, editors. RoboCup-98: Robot Soccer World Cup II. Lecture Note in Artificial Intelligence 1604. Springer, 1999.
S. Behnke, B. Frötschl, R. Rojas, P. Ackers, W. Lindstrot, M. de Melo, M. Preier, A. Schebesch, M. Simon, M. Sprengel, and O. Tenchio. Using hierarchical dynamical systems to control reactive bahaviors. In Proceedings IJCAI’99 — International Joint Conference on Artificial Intelligence, The Third International Workshop on RoboCup — Stockholm, pages 28–33, 1999.
R.A. Brooks. Intelligence without reason. A.I. Memo 1293, MIT Artificial Intelligence Lab, 1991.
T. Christaller. Cognitive robotics: A new approach to artificial intelligence. Artificial Life and Robotics, (3), 1999.
J.C. Gallagher and R.D. Beer. Evolution and analysis of dynamical neural networks for agents integrating vision, locomotion and short-term memory. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-99) — Orlando, pages 1273–1280, 1999.
H. Jäger. The dual dynamics design scheme for behavior-based robots: A tutorial. Arbeitspapier 966, GMD, 1996.
H. Jäger and T. Christaller. Dual dynamics: Designing behavior systems for autonomous robots. In S. Fujimura and M. Sugisaka, editors, Proceedings International Symposium on Artificial Life and Robotics (AROB’ 97) — Beppu, Japan, pages 76–79, 1997.
R. Pfeifer and C. Scheier. Understanding Intelligence. MIT press, Cambridge, 1998.
E. Schlottmann, D. Spenneberg, M. Pauer, T. Christaller, and K. Dautenhahn. A modular design approach towards behaviour oriented robotics. Arbeitspapier 1088, GMD, 1997.
L. Steels. The PDL reference manual. AI Lab Memo 92–5, VUB Brussels, 1992.
L. Steels. Building agents with autonomous behavior systems. In L. Steels and R.A. Brooks, editors, The ‘Artificial Life’ route to ’‘Artificial Intelligence’: Building situated embodied agents. Lawrence Erlbaum Associates, New Haven, 1994.
A. Steinhage. Nonlinear attractor dynamics: A new approach to sensor fusion. In P.S. Schenker and G.T. McKee, editors, Sensor Fusion and Decentralized Control in Robotic Systems II: Proceedings of SPIE, volume 3839, pages 31–42. Spiepublishing, 1999.
A. Steinhage and T. Bergener. Learning by doing: A dynamic architecture for generating adaptive behavioral sequences. In Proceedings of the Second ICSC Symposium on Neural Computation NC2000 — Berlin, pages 813–820, 2000.
A. Steinhage and G. Schöner. The dynamic approach to autonomous robot navigation. In Proceedings of the IEEE International Symposium on Industrial Electronics ISIE’97, pages SS7–SS12, 1997.
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Behnke, S., Rojas, R. (2001). A Hierarchy of Reactive Behaviors Handles Complexity. In: Balancing Reactivity and Social Deliberation in Multi-Agent Systems. BRSDMAS 2000. Lecture Notes in Computer Science(), vol 2103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44568-4_8
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DOI: https://doi.org/10.1007/3-540-44568-4_8
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