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MIRO : An Embedded Distributed Architecture for Biologically inspired Mobile Robots

Nature has always been a source of inspiration in the development of robotic systems. As such, the study of animal behavior (ethology) and the study of the underlying neural structure responsible for behavior (neuroethology) have inspired many robotic designs. In general, neuroethological based systems tend to be more complex than ethological ones thus being more expensive to compute, a common problem to both simulation and robotic experimentation. To overcome this problem, it is necessary either to incorporate very powerful hardware or, particularly in the case of mobile robots, embed the robot via wireless communication into remote distributed computational system where expensive computation can take place. While the first approach simplifies the overall robotic architecture it results in bulky and expensive robots. The second approach results in smaller and less expensive robots, although involving more complex architectures. The work presented in this paper discusses the second approach that of embedding mobile robots to distributed computational systems. We describe our current work in conducting neuroethological robotic experimentation using the MIRO (Mobile Internet Robotics) system linked to the NSL/ASL neural simulation system. In optimizing overall system performance, communication between the robot and the computing system is managed by an Adaptive Robotic Middleware (ARM).