2015
A convex relaxation for approximate global optimization in simultaneous localization and mapping
ICRA 2015poster
Modern approaches to simultaneous localization and mapping (SLAM) formulate the inference problem as a high-dimensional but sparse nonconvex M-estimation, and then apply general first- or second-order smooth optimization methods to recover a local minimizer of the objective function. The performance…