Integration of Coordination Architecture and Behavior Fuzzy Learning in Quadruped Walking Robots

This paper presents the design and implementation of a coordination architecture for quadruped walking robots to learn and execute soccer-playing behaviors. A typical hybrid architecture combing reactive behaviors with deliberative reasoning is developed. The reactive behaviors directly map spatial information extracted from sensors into actions. The deliberative reasoning represents temporal constraints of a robot´s strategy in terms of finite state machines. In order to achieve real-time and robust control performance in reactive behaviors, fuzzy logic controllers (FLCs) are used to encode the behaviors, and a two-stage learning scheme is adopted to make these FLCs adaptive to complex situations. The experimental results are provided to show the suitability of the architecture and effectiveness of the proposed learning scheme.