Conic Feature Based Simultaneous Localization and Mapping in Open Environment via 2D Lidar

The conventional planar scan matching approach cannot cope well with the open environment as lacking of sufficient edges and corners. This paper presents a conic feature based simultaneous localization and mapping (SLAM) algorithm via 2D lidar which can adapt to an open environment nicely. The novelty of this work includes threefold: (1) defining a conic feature based parametrization approach; (2) developing a method to utilize feature's conic geometric information and odometry information since open environments are short of regular linear geometric features; (3) developing a factor graph based framework which can be adapted with the proposed parametrization. Simulation experiments and real environment experiments demonstrated that the proposed SLAM algorithm can get accurate and convincing results for the open environment and the map in our representation can express accurately the environment situation.