The proposed algorithm is a fast evolution-based vision technique for real-time obstacle detection. Based on the Parisian approach, our algorithm evolves a population of 3D particles which constitutes a three-dimensional representation of the scene. Evolution is controlled by a fuzzy fitness function able to deal with uncertain camera measurements, and uses classical evolutionary operators. The result of the algorithm is a set of 3D particles gathered on the surfaces of obstacles.