The invention discloses an MB-RRT-based unmanned aerial vehicle two-dimensional track planning method, comprising the steps of initializing a tree and environmental information; importing obstacle information, and setting a number of iterations; judging whether the number of iterations is arrived, if so, performing down-sampling on the generated path point and optimizing the generated path line by adopting an interpolation algorithm; otherwise, generating a random sampling point, looking for a point nearest to the random sampling point in the tree, generating an adaptive step length according to the point, generating a final interpolation point according to the step length, judging whether the distance between the interpolation point and the root is greater than the current optimal path length, if not, performing collision detection on the path, adding the interpolation point to the tree and optimizing adjacent nodes around the interpolation point; if not, performing connection detection and connection on the tree. The method is high in convergence rate and small in memory occupation space, solves the problem of limitation of growth nearby an obstacle, and can be directly applied to unmanned aerial vehicle control.