CNN wave based computation for robot navigation planning

In this work a methodology for real-time robot navigation in a complex, dynamically changing environment, based on wave computation and implemented by cellular neural networks (CNNs) is introduced. The keypoint of the approach is to consider the environment in which the robot moves as an excitable medium. Obstacles and targets represent the source of autowave generation. The wavefronts propagating in the CNN medium provide to the robot all the information to achieve an adaptive motion avoiding the obstacles and directed to the target. In particular the paradigm of reaction-diffusion (RD) equations are used to implement a CNN-based wave computation for navigation control. Experimental results validating the approach are shown.