A method for the collaborative readjustment of platforms in a network comprising at least two platforms (10 1 , 10 2 ) and at least one landmark (20 1 ), the positions of the platforms and landmarks being known but inaccurate, the at least one landmark being visible to the platforms that exchange information by means of a communication protocol, said method containing at least the following steps: considering a state vector u consisting of the positions of the platforms and of the landmark(s), determining an observation vector m of dimension equal to 2M + K + L measurements, with: - M measurements of position of the platforms and of the landmark(s): one measurement of position per platform and one measurement of position per landmark, - L measurements of angles performed for pairs of platform/landmark entities with at most one angle measurement for each pair of platform/landmark entities, - K measurements of distances between pairs of platform/landmark entities, estimating the state vector u of dimension 2M using a maximum likelihood criterion that takes into account the observation vector m, deducing, from the estimated state vector and jointly, the coordinates of the positions of the at least two platforms and of the landmark(s), and transmitting these new coordinates to the platforms and landmarks in contact with said readjusted platforms; according to which the state vector u is estimated according to one or the other of the following provision: - 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 is the covariance matrix of the measurements, h(u) the global observation function of the state vector u , T the transpose. considering a state vector u consisting of the positions of the platforms and of the landmark(s), determining an observation vector m of dimension equal to 2M + K + L measurements, with: - M measurements of position of the platforms and of the landmark(s): one measurement of position per platform and one measurement of position per landmark, - L measurements of angles performed for pairs of platform/landmark entities with at most one angle measurement for each pair of platform/landmark entities, - K measurements of distances between pairs of platform/landmark entities, - M measurements of position of the platforms and of the landmark(s): one measurement of position per platform and one measurement of position per landmark, - L measurements of angles performed for pairs of platform/landmark entities with at most one angle measurement for each pair of platform/landmark entities, - K measurements of distances between pairs of platform/landmark entities, estimating the state vector u of dimension 2M using a maximum likelihood criterion that takes into account the observation vector m, deducing, from the estimated state vector and jointly, the coordinates of the positions of the at least two platforms and of the landmark(s), and transmitting these new coordinates to the platforms and landmarks in contact with said readjusted platforms; according to which the state vector u is estimated according to one or the other of the following provision: - 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 is the covariance matrix of the measurements, h(u) the global observation function of the state vector u , T the transpose. <EOS>