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Proceedings ArticleDOI

How MuCAR won the convoy scenario at ELROB 2016

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TLDR
The hard- and software system of MuCAR, the new multi-sensor data fusion method as well as the challenging situations during the ELROB 2016 robotics trial are described aswell as the challenges faced during the competition.
Abstract
Team MuCAR participated in the convoy scenario within the ELROB 2016 robotics trial and achieved the best score overall. This paper describes the hard- and software system of MuCAR, our new multi-sensor data fusion method as well as the challenging situations during the competition. The competition took place in an unstructured environment without lane markings and with dynamic objects. Autonomous following of a specific convoy leader and detecting hazardous environments in the form of ERICard associated warning signs were the main tasks of the convoy scenario. In order to achieve high robustness, we present a module which fuses the measurement data of different sensors and tracking modules at object level. In comparison to other participants, our team was able to drive the course without any manual interventions. Additionally, we were the only team which could detect all ERICards completely autonomously.

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References
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Proceedings Article

Fast approximate nearest neighbors with automatic algorithm configuration

TL;DR: A system that answers the question, “What is the fastest approximate nearest-neighbor algorithm for my data?” and a new algorithm that applies priority search on hierarchical k-means trees, which is found to provide the best known performance on many datasets.
Journal ArticleDOI

Topological Structural Analysis of Digitized Binary Images by Border Following

TL;DR: Two border following algorithms are proposed for the topological analysis of digitized binary images, which determine the surroundness relations among the borders of a binary image and follow only the outermost borders.
Journal ArticleDOI

The Gaussian Mixture Probability Hypothesis Density Filter

TL;DR: Under linear, Gaussian assumptions on the target dynamics and birth process, the posterior intensity at any time step is a Gaussian mixture and closed-form recursions for propagating the means, covariances, and weights of the constituent Gaussian components of the posteriorintensity are derived.
Book

Robotic mapping: a survey

TL;DR: This article provides a comprehensive introduction into the field of robotic mapping, with a focus on indoor mapping, and describes and compares various probabilistic techniques, as they are presently being applied to a vast array of mobile robot mapping problems.
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