Konzeption eines kamerabasierten kollisionswarnsys-tems zur prävention von arbeitsunfällen an gabelstaplern

Armin Lang; Johannes Fottner

doi:10.2195/lj_Proc_lang_de_201710_01

Konzeption eines kamerabasierten kollisionswarnsys-tems zur prävention von arbeitsunfällen an gabelstaplern

Armin Lang
, Johannes Fottner

Lehrstuhl für Fördertechnik Materialfluss Logistik

Technische Universität München

Publikation: Beitrag in Fachzeitschrift › Artikel › Begutachtung

4 Zitate (Scopus)

Abstract

This paper introduces a method to reduce occupational accidents caused by forklift trucks. The conceptual system detects collisions by calculating movement vectors of all objects being in the sight of the camera. Moreover the system is capable to distinguish between humans and warehouse accommodation. The latter enables the feasibility of a more sensitive warning when a human is endangered.

Titel in Übersetzung	Conception of a camera-based collision warning system for prevention of occupational accidents caused by forklift trucks
Originalsprache	Deutsch
Fachzeitschrift	Logistics Journal
Jahrgang	2017
DOIs	https://doi.org/10.2195/lj_Proc_lang_de_201710_01
Publikationsstatus	Veröffentlicht - 16 Okt. 2017

Schlagwörter

Collision
Computer vision
Driver assistance system
Forklift truck
Machine learning

Zugriff auf Dokument

10.2195/lj_Proc_lang_de_201710_01

Andere Dateien und Links

Verknüpfung zur Publikation in Scopus

Dieses zitieren

@article{4549846faa4b43d38cc173076ff7e4a2,

title = "Konzeption eines kamerabasierten kollisionswarnsys-tems zur pr{\"a}vention von arbeitsunf{\"a}llen an gabelstaplern",

abstract = "This paper introduces a method to reduce occupational accidents caused by forklift trucks. The conceptual system detects collisions by calculating movement vectors of all objects being in the sight of the camera. Moreover the system is capable to distinguish between humans and warehouse accommodation. The latter enables the feasibility of a more sensitive warning when a human is endangered.",

keywords = "Collision, Computer vision, Driver assistance system, Forklift truck, Machine learning",

author = "Armin Lang and Johannes Fottner",

note = "Publisher Copyright: {\textcopyright} 2017 Logistics Journal.",

year = "2017",

month = oct,

day = "16",

doi = "10.2195/lj\_Proc\_lang\_de\_201710\_01",

language = "Deutsch",

volume = "2017",

journal = "Logistics Journal",

issn = "1860-7977",

publisher = "Wissenschaftliche Gesellschaft fur Technische Logistik",

}

TY - JOUR

T1 - Konzeption eines kamerabasierten kollisionswarnsys-tems zur prävention von arbeitsunfällen an gabelstaplern

AU - Lang, Armin

AU - Fottner, Johannes

PY - 2017/10/16

Y1 - 2017/10/16

N2 - This paper introduces a method to reduce occupational accidents caused by forklift trucks. The conceptual system detects collisions by calculating movement vectors of all objects being in the sight of the camera. Moreover the system is capable to distinguish between humans and warehouse accommodation. The latter enables the feasibility of a more sensitive warning when a human is endangered.

AB - This paper introduces a method to reduce occupational accidents caused by forklift trucks. The conceptual system detects collisions by calculating movement vectors of all objects being in the sight of the camera. Moreover the system is capable to distinguish between humans and warehouse accommodation. The latter enables the feasibility of a more sensitive warning when a human is endangered.

KW - Collision

KW - Computer vision

KW - Driver assistance system

KW - Forklift truck

KW - Machine learning

UR - https://www.scopus.com/pages/publications/85034421510

U2 - 10.2195/lj_Proc_lang_de_201710_01

DO - 10.2195/lj_Proc_lang_de_201710_01

M3 - Artikel

AN - SCOPUS:85034421510

SN - 1860-7977

VL - 2017

JO - Logistics Journal

JF - Logistics Journal

ER -

Konzeption eines kamerabasierten kollisionswarnsys-tems zur prävention von arbeitsunfällen an gabelstaplern

Abstract

Schlagwörter

Zugriff auf Dokument

Andere Dateien und Links

Fingerprint

Dieses zitieren