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In order to detect and track pedestrians in complex indoor backgrounds, a pedestrian detection and tracking method for indoor robots equipped with Laser radar is proposed. Firstly, The SLAM (Simultaneous Location and Mapping) technology is applied to obtain 2D grid map for a strange environment; then, Monte Carlo localization is employed to obtain the posterior pose of the robot in the map; then, an improved likelihood field background subtraction algorithm is proposed to extract the interesting foreground in changeable environment; then, the hierarchical clustering algorithm combining with an improved leg model is proposed to detect the objective pedestrian; at last, an improved tracking intensity formula is designed to track and follow the objective pedestrian. Experimental results in some complex environments show that our method can effectively reduce the impact of confusing scenarios which are challenges for other algorithms, such as the motion of the chair, the suddenly passing by person and when the objective pedestrian close to the wall and so on, and can detect, track and follow pedestrians in real time with high accuracy.

A Pedestrian Detection and Tracking Method for Robot Equipped with Laser Radar