TY  - JOUR
A1  - Claer, Mario
A1  - Ferrein, Alexander
A1  - Schiffer, Stefan
T1  - Calibration of a Rotating or Revolving Platform with a LiDAR Sensor
JF  - Applied Sciences
Y1  - 2019
U6  - http://dx.doi.org/10.3390/app9112238
SN  - 2076-3417
VL  - Volume 9
IS  - issue 11, 2238
PB  - MDPI
CY  - Basel
ER  - 
TY  - JOUR
A1  - Schulte-Tigges, Joschua
A1  - Förster, Marco
A1  - Nikolovski, Gjorgji
A1  - Reke, Michael
A1  - Ferrein, Alexander
A1  - Kaszner, Daniel
A1  - Matheis, Dominik
A1  - Walter, Thomas
T1  - Benchmarking of various LiDAR sensors for use in self-driving vehicles in real-world environments
JF  - Sensors
N2  - Abstract
In this paper, we report on our benchmark results of the LiDAR sensors Livox Horizon, Robosense M1, Blickfeld Cube, Blickfeld Cube Range, Velodyne Velarray H800, and Innoviz Pro. The idea was to test the sensors in different typical scenarios that were defined with real-world use cases in mind, in order to find a sensor that meet the requirements of self-driving vehicles. For this, we defined static and dynamic benchmark scenarios. In the static scenarios, both LiDAR and the detection target do not move during the measurement. In dynamic scenarios, the LiDAR sensor was mounted on the vehicle which was driving toward the detection target. We tested all mentioned LiDAR sensors in both scenarios, show the results regarding the detection accuracy of the targets, and discuss their usefulness for deployment in self-driving cars.
KW  - Lidar
KW  - Benchmark
KW  - Self-driving
Y1  - 2022
U6  - http://dx.doi.org/10.3390/s22197146
SN  - 1424-8220
N1  - This article belongs to the Special Issue "Sensor Fusion for Vehicles Navigation and Robotic Systems"
VL  - 22
IS  - 19
PB  - MDPI
CY  - Basel
ER  - 
TY  - JOUR
A1  - Ulmer, Jessica
A1  - Braun, Carsten
A1  - Cheng, Chi-Tsun
A1  - Dowey, Steve
A1  - Wollert, Jörg
T1  - A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation
JF  - International Journal of Production Research
N2  - Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers’ cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines.
KW  - Human factors
KW  - assistance system
KW  - gamification
KW  - adaptive systems
KW  - manufacturing
Y1  - 2023
U6  - http://dx.doi.org/10.1080/00207543.2023.2166140
SN  - 0020-7543 (Print)
SN  - 1366-588X (Online)
PB  - Taylor & Francis
ER  - 
TY  - JOUR
A1  - Ferrein, Alexander
A1  - Steinbauer, Gerald
T1  - 20 Years of RoboCup -  A Subjective Retrospection
JF  - KI - Künstliche Intelligenz
N2  - This summer, RoboCup competitions were held for the 20th time in Leipzig, Germany. It was the second time that RoboCup took place in Germany, 10 years after the 2006 RoboCup in Bremen. In this article, we give an overview on the latest developments of RoboCup and what happened in the different leagues over the last decade. With its 20th edition, RoboCup clearly is a success story and a role model for robotics competitions. From our personal view point, we acknowledge this by giving a retrospection about what makes RoboCup such a success.
Y1  - 2016
U6  - http://dx.doi.org/10.1007/s13218-016-0449-5
SN  - 1610-1987
VL  - 30
IS  - 3
SP  - 225
EP  - 232
PB  - Springer
CY  - Berlin
ER  - 
TY  - JOUR
A1  - Steinbauer, Gerald
A1  - Ferrein, Alexander
T1  - 20 Years of RoboCup
JF  - KI - Künstliche Intelligenz
Y1  - 2016
U6  - http://dx.doi.org/10.1007/s13218-016-0442-z
SN  - 1610-1987
VL  - 30
IS  - 3-4
SP  - 221
EP  - 224
PB  - Springer
CY  - Berlin
ER  -