2026-05-28T13:12:42Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/115142026-02-03T12:06:13Zcom_10630_2254col_10630_37959

Jaimez, Mariano González-Monroy, Javier González-Jiménez, Antonio Javier 2016-05-27T06:35:46Z 2016-05-27T06:35:46Z 2016 http://hdl.handle.net/10630/11514 http://orcid.org/0000-0003-3845-3497 In this paper we present a fast and precise method to estimate the planar motion of a lidar from consecutive range scans. For every scanned point we formulate the range flow constraint equation in terms of the sensor velocity, and minimize a robust function of the resulting geometric constraints to obtain the motion estimate. Conversely to traditional approaches, this method does not search for correspondences but performs dense scan alignment based on the scan gradients, in the fashion of dense 3D visual odometry. The minimization problem is solved in a coarse-to-fine scheme to cope with large displacements, and a smooth filter based on the covariance of the estimate is employed to handle uncertainty in unconstraint scenarios (e.g. corridors). Simulated and real experiments have been performed to compare our approach with two prominent scan matchers and with wheel odometry. Quantitative and qualitative results demonstrate the superior performance of our approach which, along with its very low computational cost (0.9 milliseconds on a single CPU core), makes it suitable for those robotic applications that require planar odometry. For this purpose, we also provide the code so that the robotics community can benefit from it. eng open access by-nc Robótica Planar Odometry from a Radial Laser Scanner. A Range Flow-based Approach conference output