NDLI: Object tracking with enhanced data association using a 3D range sensor for an unmanned ground vehicle

Content Provider	Springer Nature Link
Author	Cho, Kuk Baeg, SeungHo Park, Sangdeok
Copyright Year	2014
Abstract	This paper describes a novel object tracking method which combines a conventional global nearest-neighbor (GNN) method with an enhanced data association approach using 3D data features for an unmanned ground vehicle. If an object crosses in front of an observation system which has a measurement sensor equipped on a vehicle, a conventional distance-based object tracking mechanism encounters a data association problem owing to high uncertainties and a leak of information: correspondence between observations and tracks. To overcome these correspondence problems, we use the object’s 3D information such as statistical and geometrical information. In this paper, we describe a clustering and segmentation processes in conjunction with a distance-based nearest-neighbor approach, RBNN-2, and applied GNN with enhanced data association using both a kinematic and geometric models derived from 3D range data. To evaluate our method using a 3D LADAR sensor, a Velodyne HDL-32e, installed on the vehicle, we conducted an experiment involving two crossing humans and a ground vehicle to identify different human trajectories for a leader-following system.
Starting Page	4381
Ending Page	4388
Page Count	8
File Format	PDF
ISSN	1738494X
Journal	Journal of Mechanical Science and Technology
Volume Number	28
Issue Number	11
e-ISSN	19763824
Language	English
Publisher	Korean Society of Mechanical Engineers
Publisher Date	2015-01-22
Publisher Place	Seoul
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	3D LADAR Object tracking Data association Mechanical Engineering Vibration, Dynamical Systems, Control Industrial and Production Engineering
Content Type	Text
Resource Type	Article
Subject	Mechanics of Materials Mechanical Engineering

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