This paper introduces a simple algorithm to solve robot path finding problem using active wave computing
techniques. A two-dimensional Cellular Neural/Nonlinear Network (CNN), consist of relaxation oscillators,
has been used to generate active waves and to process the visual information. The network, which has been
implemented on a Field Programmable Gate Array (FPGA) chip, has the feature of being programmed, controlled
and observed by a host computer. The arena of the robot is modelled as the medium of the active waves on
the network. Active waves are employed to cover the whole medium with their own dynamics, by starting from
an initial point. The proposed algorithm is achieved by observing the motion of the wave-front of the active
waves. Host program first loads the arena model onto the active wave generator network and command to start
the generation. Then periodically pulls the network image from the generator hardware to analyze evolution of
the active waves. When the algorithm is completed, vectorial data image is generated. The path from any of
the pixel on this image to the active wave generating pixel is drawn by the vectors on this image. The robot
arena may be a complicated labyrinth or may have a simple geometry. But, the arena surface always must be
flat. Our Autowave Generator CNN implementation which is settled on the Xilinx University Program Virtex-II
Pro Development System is operated by a MATLAB program running on the host computer. As the active
wave generator hardware has 16, 384 neurons, an arena with 128 × 128 pixels can be modeled and solved by the
algorithm. The system also has a monitor and network image is depicted on the monitor simultaneously.
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