Particle filter-based perception method for obstacles in dynamic environment of a mobile robot

Abstract

The state perception problem for obstacles occurring in the workspace of a mobile robot is a challenging task. The main goal of this work is to introduce a novel concept of the Particle filter algorithm where not only the positions but also the velocities of static and moving obstacles can be perceived using measurement data of an onboard LiDAR sensor. Next to the well-known resampling methods, a novel resampling algorithm was also introduced where the effective number of the particles can be considered. The introduced algorithm can generate an appropriate solution for both the position and velocity perception task.