Mobile robotic path planning is a critical issue in today’s world of automation. While many algorithms are available to address this challenge, the optimization and efficiency of each algorithm varies according to the techniques employed in the algorithms. The paper aims to compare three different algorithms namely the conventional A* algorithm, fuzzy-based soft computing methods and advanced strategy-based optimization technique namely the min–max approach of Game Theory (GT). In this work, several number of obstacles like two, four, six, eight and ten are simulated in the path of the robot and an analysis with the techniques and the time elapsed for each algorithm in the same framework is compared and it is found that the advanced method of GT based pathfinding is superior over others and can be employed for real-time implementation.