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Motion planning is an important step in any complex robotic motion task. Many algorithms deal with this problem and a lot of effective approaches makes use of random generation of roadmaps or motion commands. In this paper, a novel algorithm for random roadmap generation is proposed. This approach, which addresses the planning problem with a resilience philosophy, relies on a network model with some particular topological properties. These properties of robustness against random faults and intentional attacks are functional to devising a suitable solution for the planning problem. Comparative simulations against several algorithms have been performed to show the effectiveness of the proposed approach.