A Multi-level Approach to Biologically Inspired Robotic Systems

摘要

The study of biological systems has inspired the development of a large number of neural network architectures and robotic implementations. Through both experimentation and simulation biological systems provides a means to understand the underlying mechanisms in living organisms while inspiring the development of robotic applications. Experimentation, in the form of data gathering (ethological physiological and anatomical), provides the underlying data for simulation generating predictions to be validated by theoretical models. These models provide the understanding for the underlying neural dynamics, and serve as basis for simulation and robotic experimentation. Due to the inherent complexity of these systems, a multi-level analysis approach is required where biological, theoretic and robotic systems are studied at different levels of granularity. The work presented here overviews our existing modeling approach and describes current simulation results.