Many real-world applications of robot path planning involves not only finding the shortest path, but also achieving some other objectives such as minimizing fuel consumption or avoiding danger areas. This paper introduces a 2D path planning scheme that solves a multi-objective path planning problem on a 3D terrain. This allows the controller to pick the most suitable path among a set of optimal paths. The algorithm generates a cellular automaton for the terrain based on the objectives by applying various weighting factors via an evolutionary algorithm and finds the optimal path between the start point and the goal for each set of parameters considering static obstacles and maximum slope constraints. All the final trajectories share the same characteristic that they are non-dominated with respect to the rest of the set in the Multi-Objective Optimization Problems (MOP) context. The objectives considered in this study includes the path length, the elevation changes and avoiding the radars. Testing the algorithm on several problems showed that the method is very promising for mobile robot path planning applications.

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