Automata-Driven Fire Rescue Bot: Leveraging NFA and TM for Efficient Pathfinding

This chapter delves into the critical aspects of robotic fire rescue missions, focusing on computation, real-time decision-making, and object detection. It explores the use of non-deterministic finite automata (NFA) and Turing machines (TM) for efficient pathfinding in dynamic and unpredictable fire-affected environments. The article provides a comprehensive literature survey, highlighting the state-of-the-art in formal automata theory and robotics, and identifies gaps in current research. The methodology section outlines the procedure for designing and testing NFA and TM using JFLAP and Pygame simulations, drawing a comparison between their performances. The results and discussions section presents testing sequences and simulations, demonstrating the effectiveness of NFA and TM in various scenarios. The chapter concludes with a summary of the key differences between NFA and TM, emphasizing their respective advantages and limitations in robotic fire rescue missions.