Modeling systems in terms of a Petri net (PN) provides a better understanding of the specific actions and sequence in which they need to be carried out by utilizing PN’s powerful analytical capabilities. However, because of the uncertainty present in many real world applications, it is not straightforward to use PNs in modeling and simulation of a system. The integration of PNs with fuzzy logic presents Fuzzy Petri nets (FPNs). Fuzzy logic is introduced as the programming logic of choice for modeling a self-navigating robot algorithm due to its versatile multi-valued logic reasoning. By using FPNs, it is possible to simulate, assess, and communicate the process and reasoning of the navigational algorithm and apply it to real world programming. In this paper, we propose Trilateral Distance Sensor Based (TDSeB) and Flame and Reflection Detection (FReD) algorithms in order to optimize the sequence of actions of a robot for completing the given task. As a result of modeling and simulation, the proposed algorithms have outperformed non-systematic methods by 17%. We also present an implementation scheme using 8-bit binary codes.