@book{2021:steyer:gridbased,
title = {Grid-Based Object Tracking},
year = {2021},
note = {Mobile robots require an accurate environment perception to plan
intelligent maneuvers and avoid collisions. This thesis presents a
novel multi sensor environment estimation strategy that fully combines
tracking moving objects and mapping the static environment. The basic
idea is to fuse and accumulate measurement data by a dynamic occupancy
grid model, whereas moving objects are extracted subsequently based on
that generic low-level grid representation. Overall, this work results
in a robust and consistent estimation of arbitrary objects and
obstacles, which is demonstrated in the context of autonomous driving
in complex unstructured environments.ContentsNotations VIIIAbstract
XI1 Introduction 11.1 Motivation . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . 11.2 Challenges of Multi-Sensor
Environment Perception . . . . . . . . . . . . . 21.3 Main
Contribution and Outline of This Work . . . . . . . . . . . . . . . .
82 Measurement Grid Representation and Fusion 132.1 Introduction . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
132.1.1 Related Work . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . 132.1.2...},
edition = {1},
publisher = {VDI Verlag},
address = {Düsseldorf},
series = {Mess-, Steuerungs- und Regelungstechnik},
volume = {1272},
author = {Steyer, Sascha}
}