A method for the collaborative readjustment of platforms in a network comprising M platforms (10 1 , 10 2 ) whose positions are known with a certain degree of inaccuracy, M being greater than or equal to two, and I landmarks (20 1 ), whose positions are unknown, visible to the M platforms, I being greater than or equal to one, said platforms exchanging information, said method containing at least the following steps: considering a state vector u consisting of the positions of the M platforms and I landmarks, determining an observation vector m of dimension equal to 2M + K + L, with: - M measurements of position of the platforms, - L measurements of angles between pairs of platform/landmark entities with at most one angle measurement for each pair of platform/landmark entity, - K measurements of distances between pairs of platform/landmark entities, estimating the state vector u of dimension 2(M + I) using a maximum likelihood criterion that takes into account the observation vector m, deducing simultaneously, from the estimated state vector, the coordinates of the positions of the platforms and of the landmarks, and transmitting the new coordinates of each readjusted platform to the platforms and landmarks in contact with said platform, according to which state vector u is estimated according to one of the two following provisions: - by maximising the probability: p m / u = 1 2 π N 2 B 1 / 2 exp − 1 2 m − h u T B − 1 m − h u - by minimising the quadratic form: Q u = m − h u T B − 1 m − h u N being the dimension of the observation vector, B the covariance matrix of the measurements, h ( u ), the global observation function of u, T the transpose. considering a state vector u consisting of the positions of the M platforms and I landmarks, determining an observation vector m of dimension equal to 2M + K + L, with: - M measurements of position of the platforms, - L measurements of angles between pairs of platform/landmark entities with at most one angle measurement for each pair of platform/landmark entity, - K measurements of distances between pairs of platform/landmark entities, - M measurements of position of the platforms, - L measurements of angles between pairs of platform/landmark entities with at most one angle measurement for each pair of platform/landmark entity, - K measurements of distances between pairs of platform/landmark entities, estimating the state vector u of dimension 2(M + I) using a maximum likelihood criterion that takes into account the observation vector m, deducing simultaneously, from the estimated state vector, the coordinates of the positions of the platforms and of the landmarks, and transmitting the new coordinates of each readjusted platform to the platforms and landmarks in contact with said platform, according to which state vector u is estimated according to one of the two following provisions: - by maximising the probability: p m / u = 1 2 π N 2 B 1 / 2 exp − 1 2 m − h u T B − 1 m − h u - by minimising the quadratic form: Q u = m − h u T B − 1 m − h u - by maximising the probability: p m / u = 1 2 π N 2 B 1 / 2 exp − 1 2 m − h u T B − 1 m − h u - by minimising the quadratic form: Q u = m − h u T B − 1 m − h u N being the dimension of the observation vector, B the covariance matrix of the measurements, h ( u ), the global observation function of u, T the transpose. <EOS>