Path planning is a critical aspect of robotics research, essential for navigating manipulators efficiently through intricate environments. Despite the plethora of theoretical methods proposed in the literature, the translation of these theories into practical solutions remains a formidable challenge. This paper presents a thorough investigation into path-planning techniques for multi-degree-of-freedom (DOF) robotic manipulators, aiming to narrow the gap between theory and practical implementation. Through a series of experiments and simulations, we assess the effectiveness of various path-planning methods and evaluate their suitability for real-world applications. Our research emphasizes the utilization of existing theoretical frameworks, adapted to develop practical models capable of addressing real-life challenges. By scrutinizing the feasibility and performance of different approaches, we offer insights into the effective implementation of theoretical solutions to tackle practical problems in robotics. The findings of this study contribute to the advancement of path planning and provide valuable guidance for designing robust and efficient robotic systems.