A prey catching and predator avoidance neural-schema architecture for single and multiple robots
The paper presents a biologically inspired multi-level neural-schema architecture for prey catching and predator avoidance in single and multiple autonomous robotic systems. The architecture is inspired on anuran (frogs and toads) neuroethological studies and wolf pack group behaviors. The single robot architecture exploits visuomotor coordination models developed to explain anuran behavior in the presence of preys and predators. The multiple robot architecture extends the individual prey catching and predator avoidance model to experiment with group behavior. The robotic modeling architecture distinguishes between higher-level schemas representing behavior and lower-level neural structures representing brain regions. We present results from single and multiple robot experiments developed using the NSL/ASL/MIRO system and Sony AIBO ERS-210 robots.
prey catching predator avoidance schemas behaviors biorobotics biologically inspired robotics neural networks swarms