Comparison between Off-line Model-Free and On-line Model-Based Evolution Applied to a Robotics Navigation System Using Evolvable Hardware
Recently there has been great interest in the idea that evolvable systems based on the principles of Artificial Life can be used to continuously and autonomously adapt the behavior of physically embedded systems such as mobile robots, plants and intelligent home devices. At the same time, we have seen the introduction of evolvable hardware (EHW): new integrated circuits that are able to adapt their hardware autonomously and almost continuously to changes in the environment. This paper describes how a navigation system for a physical mobile robot can be evolved using a dynamic Boolean function approach implemented on evolvable hardware. The task of the mobile robot is to track a moving target represented by a colored ball, while avoiding obstacles during its motion in a non-deterministic and not stationary environment. Our results show that a dynamic Boolean function approach is sufficient to produce this navigation behavior. Although the classical model-free evolution method is often infeasible in the real world due to the number of possible interactions with the environment, we demonstrate that a model-based evolution method can reduce the interactions with the real world by a factor of 250, thus allowing us to apply the evolution process on-line and to obtain an adaptive tracking-avoiding system, provided the implementation can be accelerated by the utilization of evolvable hardware.
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