Incorporating Moving Landmarks within 2D Graph-Based SLAM for Dynamic Environments

In recent years, Simultaneous Localisation and Mapping (SLAM) in dynamic environments received more and more attention. Most approaches focus on efficiently removing dynamic objects present within the scene to perform SLAM with the assumption of a static environment. Some approaches incorporate dynamic objects within the optimization problem to perform SLAM and dynamic object tracking concurrently. In this paper, we propose to incorporate information from dynamic objects into a 2D graph-based SLAM approach. We experimentally show that, by adding a measurement function of the dynamic objects to the front-end graph structure, and adopting a motion model of the object, the trajectory of the dynamic object as well as the robot's trajectory can be substantially improved in the absence of static features within the graph. Experimental results based on simulated data and data from a differential drive robot with a LiDAR sensor validate this approach.