The Rapidly Exploring Random Tree Star (RRT∗) is an extension of the Rapidly Exploring Random Tree path finding algorithm. RRT∗ guarantees an optimal, collision free path solution but is limited by slow convergence rates and inefficient memory utilization. This paper presents APGD-RRT∗, a variant of RRT∗ which utilizes Artificial Potential Fields to improve RRT∗ performance, providing relatively better convergence rates. Simulation results under different environments between the proposed APGD-RRT∗ and RRT∗ algorithms demonstrate this marked improvement under various test environments.