The disclosure relates to motion planning for autonomous vehicles to find a contiguous path to travel from a source to a destination in a real time environment. But, motion planning suffers due to dimensionality problem during planning a path in high dimensional configuration space. Conventional a priori path planning techniques utilize deterministic selection of a seed and there is a challenge in providing resolution completeness, especially in a cluttered environment. Here, the resolution problem associated with the cluttered environment, is rectified by utilizing random seed generation technique. A convex region is grown around each seed and a set of hyperplanes are generated around each convex region. A contiguous polytope is created by utilizing the set of hyperplanes associated with each convex region. Further, an undirected graph is created based on a plurality of polytope points associated with the contiguous polytope and a shortest path in the graph is computed.