Fast Extended Information Filter SLAM Algorithm Based on Sparsification

With the continuous development of SLAM technology,computational efficiency has become the main obstacle in SLAM development.From the view of sparsification,an improved algorithm based on extended information filter SLAM is introduced.According to the sparsification feature of information matrix,the algorithm not only improves computation efficiency but also maintains accuracy of the estimated result through using proper sparsification of information matrix as well as loop closure detection.Four key problems of information matrix sparsification,i.e.,algorithm efficiency,relocalization,error and covariance are analyzed with simulation.Two cases are discussed through experiments,i.e.indoor two-wheel robot with camera and outdoor four-wheel robot with laser scanner,and the results of simulation and experiments verify the validity of the proposed algorithm.