This paper presents the development of a library that can be used to create path planning algorithms for robotic systems. Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) was used to create this library of path planning algorithms. Path planning algorithms that can be created using this library are Rapidly-exploring Random Tree (RRT), RRT*, RRT*-Connect, Informed RRT*, Informed RRT*-Connect, Probabilistic Roadmap (PRM), A*, Dijkstra, Particle Swarm Optimization (PSO), and the RRT-Ant Colony System (ACS). The performance of this library is evaluated by comparing the implementation of the library in benchmark scenarios from other researchers' publications. The advantages of this library are that each subprocess can be visualized, computation time is fast, tools are available for analysis, test scenarios can be created flexibly, and algorithm parameters can be easily changed to see how it affects the algorithm's output performance. Since computation time is an essential factor in path planning algorithms, the software development of this library has been streamlined to achieve the shortest possible system compute time. One way to reduce computation time is to reduce the overhead of subVI programs. SubVI overhead is reduced by making it a subroutine. The test results show that the proposed library has a faster computation time than the comparison library. The library implementation on the robotic system was tested using the LabVIEW Robotics Simulator. We also provide examples of some developments that can be done using this library. By using this library, it is hoped that students will understand and make it easier to develop path planning algorithms for robotic systems.