Abstract
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.
Highlights
Under the fast development of artificial intelligence, the research and application of intelligent service robot attracts more and more scholars and researcher’s attention, and the application fields of robots cover all aspects of human life, such as restaurant service, Home-based services, shopping guide, accompanying dance and so on [1]
In order to reduce the interference of complex background, [12] proposed a background subtraction method, which reduces the interference of background in fixed laser radar and fixed scene, but can’t be applied to mobile robot
In order to solve the problem of background interference in pedestrian detection and tracking, this paper propose a newly method, first, the environment map is constructed, and the likelihood domain model is used to segment the foreground from the background; at last, the improved Kalman filter is used to track and follow the pedestrian in the complex background
Summary
AI research center, School of Mechanical and Engineering Jiangxi college of applied technology Ganzhou, China. Abstract—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. The SLAM (Simultaneous Location and Mapping) technology is applied to obtain 2D grid map for a strange environment; Monte Carlo localization is employed to obtain the posterior pose of the robot in the map; an improved likelihood field background subtraction algorithm is proposed to extract the interesting foreground in changeable environment; 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.
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