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Carnegie Mellon Robotics Institute

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Abstract

Detection and tracking of moving objects (DATMO) in crowded urban areas from a ground vehicle at high speeds is difficult because of a wide variety of targets and uncertain pose estimation from odometry and GPS/DGPS. In this paper we present a solution of the simultaneous localization and mapping (SLAM) with DATMO problem to accomplish this task using ladar sensors and odometry. With a precise pose estimate and a surrounding map from SLAM, moving objects are detected without a priori knowledge of the targets. The interacting multiple model (IMM) estimation algorithm is used for modeling the motion of a moving object and to predict its future location. The multiple hypothesis tracking (MHT) method is applied to refine detection and data association. Experimental results demonstrate that our algorithm is reliable and robust to detect and track pedestrians and different types of moving vehicles in urban areas.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Associated Lab(s) / Group(s): NavLab

Associated Project(s): Transit Bus Collision Warning Systems and Simultaneous Localization and Mapping with Detection, Tracking, and Classification of Moving Objects

Number of pages: 6

Text Reference

Chieh-Chih Wang, Chuck Thorpe, and Arne Suppe, "Ladar-Based Detection and Tracking of Moving Objects from a Ground Vehicle at High Speeds," IEEE Intelligent Vehicles Symposium (IV2003), June, 2003.

BibTeX Reference

@inproceedings{Wang_2003_4358,
   author = "Chieh-Chih Wang and Chuck Thorpe and Arne Suppe",
   title = "Ladar-Based Detection and Tracking of Moving Objects from a Ground Vehicle at High Speeds",
   booktitle = "IEEE Intelligent Vehicles Symposium (IV2003)",
   month = "June",
   year = "2003",
}

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