Robot guiding with obstacle avoidance algorithm for uncertain enviroments based on DTCNN

This paper introduces two applications of Discrete Time Cellular Non-Linear Networks (DTCNN) in a robot guiding avoiding obstacles algorithm and prove the feasibility of both applications: a high data rate one, using a CMOS camera, and small data rate one, using ultrasonic sensors. The key value of DTCNNs is the locally connections and the parallelism in processing. These characteristics permit a hardware implementation, in our case over a Field Programmable Gate Arraw (FPGA) and a real time template based algorithm processing. A camera and an ultrasonic sensor are used as avoiding obstacles system, requiring both implementations, different inputs informations: the first one complex environment information and the later for basic situations information where impulsive response is required. Both input can have an enhanced behaviour within DTCNN structure.