Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

6-2003

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.

Keywords

Object detection, Vehicle detection, Land vehicles, Target tracking, Simultaneous localization and mapping, Urban areas, Global Positioning System, Predictive models, Laser radar, Motion estimation

Discipline

Databases and Information Systems | Graphics and Human Computer Interfaces

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the IEEE IV2003 Intelligent Vehicles Symposium, Columbus, USA, June 9-11

First Page

416

Last Page

421

ISBN

0780378482

Identifier

10.1109/IVS.2003.1212947

Publisher

IEEE

City or Country

Piscataway, NJ

Additional URL

https://doi.org/10.1109/IVS.2003.1212947

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