Fuzzy logic controller for autonomous navigation

In this correspondence, we present the performance of a low cost, fuzzy logic based controller for autonomous navigation in which the controller makes the system move through obstacles without human intervention in an efficient manner. The obstacle is sensed using a proximity sensor. We have determined the turning angle as a function of distance between the sensor and the obstacle. We evaluated the fuzzy rules for different sets of conditions. Our simulation study shows that the fuzzy algorithm outperforms the classical algorithms such as steer away from centre and steer away from surface for autonomous navigation. Further, in this correspondence, we present the way we developed the fuzzy logic controller along with liquid crystal display (LCD) controller, universal asynchronous receiver transmitter (UART), American standard code for information interchange (ASCII) to binary converter and binary to ASCII converter using verilog and implemented in Spartan 3E field programmable gate array (FPGA). It is extensively demonstrated through the implementation the way a data intensive algorithm can be coded using a hardware description language and tested on an FPGA before being tapped out into an integrated circuit (IC) in a manufacturing process.