TY  - CHAP
A1  - Zug, Sebastian
A1  - Niemueller, Tim
A1  - Hochgeschwender, Nico
A1  - Seidensticker, Kai
A1  - Seidel, Martin
A1  - Friedrich, Tim
A1  - Neumann, Tobias
A1  - Karras, Ulrich
A1  - Kraetzschmar, Gerhard K.
A1  - Ferrein, Alexander
T1  - An Integration Challenge to Bridge the Gap Among Industry-Inspired RoboCup Leagues
T2  - RoboCup 2016: Robot World Cup XX. RoboCup 2016.
Y1  - 2017
SN  - 978-3-319-68792-6
U6  - http://dx.doi.org/10.1007/978-3-319-68792-6_13
N1  - Lecture Notes in Computer Science, LNCS, Vol 9776
SP  - 157
EP  - 168
PB  - Springer
CY  - Cham
ER  - 
TY  - CHAP
A1  - Walenta, Robert
A1  - Schellekens, Twan
A1  - Ferrein, Alexander
A1  - Schiffer, Stefan
T1  - A decentralised system approach for controlling AGVs with ROS
T2  - AFRICON, Proceedings
Y1  - 2017
SN  - 978-1-5386-2775-4
U6  - http://dx.doi.org/10.1109/AFRCON.2017.8095693
SN  - 2153-0033
N1  - AFRICON <2017, 18-20 Sept., Cape Town, South Africa>
SP  - 1436
EP  - 1441
PB  - IEEE
ER  - 
TY  - JOUR
A1  - Vorst, Phillip
A1  - Ferrein, Alexander
A1  - Lakemeyer, Gerhard
T1  - AllemaniACs3D team description
Y1  - 2006
SP  - 1
EP  - 6
ER  - 
TY  - CHAP
A1  - Viehmann, Tarik
A1  - Limpert, Nicolas
A1  - Hofmann, Till
A1  - Henning, Mike
A1  - Ferrein, Alexander
A1  - Lakemeyer, Gerhard
ED  - Eguchi, Amy
ED  - Lau, Nuno
ED  - Paetzel-Prüsmann, Maike
ED  - Wanichanon, Thanapat
T1  - Winning the RoboCup logistics league with visual servoing and centralized goal reasoning
T2  - RoboCup 2022
N2  - The RoboCup Logistics League (RCLL) is a robotics competition in a production logistics scenario in the context of a Smart Factory. In the competition, a team of three robots needs to assemble products to fulfill various orders that are requested online during the game. This year, the Carologistics team was able to win the competition with a new approach to multi-agent coordination as well as significant changes to the robot’s perception unit and a pragmatic network setup using the cellular network instead of WiFi. In this paper, we describe the major components of our approach with a focus on the changes compared to the last physical competition in 2019.
Y1  - 2023
SN  - 978-3-031-28468-7 (Print)
SN  - 978-3-031-28469-4 (Online)
U6  - http://dx.doi.org/https://doi.org/10.1007/978-3-031-28469-4_25
N1  - Robot World Cup, RoboCup 2022. 17. July 2023. Bangkok, Thailand.

Part of the Lecture Notes in Computer Science book series (LNAI,volume 13561)
SP  - 300
EP  - 312
PB  - Springer
CY  - Cham
ER  - 
TY  - CHAP
A1  - Stopforth, Riaan
A1  - Ferrein, Alexander
A1  - Steinbauer, Gerald
T1  - Europe and South African collaboration on the Mechatronics and Robotics systems as part of the SA Robotics Center
T2  - ICRA 2015 Developing Countries Forum
N2  - Mechatronics consist of the integration of mechanical
engineering, electronic integration and computer science/
engineering. These broad fields are essential for robotic
systems, yet it makes it difficult for the researchers to specialize
and be experts in all these fields. Collaboration between
researchers allow for the integration of experience and specialization,
to allow optimized systems. Collaboration between the
European countries and South Africa is critical, as each country
has different resources available, which the other countries
might not have. Applications with the need for approval of
any restrictions, can also be obtained easier in some countries
compared to others, thus preventing the delays of research.
Some problems that have been experienced are discussed, with
the Robotics Center of South Africa as a possible solution.
Y1  - 2015
ER  - 
TY  - CHAP
A1  - Stopforth, Riaan
A1  - Davrajh, Shaniel
A1  - Ferrein, Alexander
T1  - South African robotics entity for a collaboration initiative
T2  - Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference (PRASA-RobMech), 2016
Y1  - 2017
SN  - 978-1-5090-3335-5
U6  - http://dx.doi.org/10.1109/RoboMech.2016.7813144
N1  - PRASA-RobMech, Nov. 30 2016-Dec. 2 2016, Stellenbosch, South Africa
SP  - 1
EP  - 6
PB  - IEEE
ER  - 
TY  - CHAP
A1  - Stopforth, Riaan
A1  - Davrajh, Shaniel
A1  - Ferrein, Alexander
T1  - Design considerations of the duo fugam dual rotor UAV
T2  - 2017 Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA-RobMech)
Y1  - 2017
SN  - 978-1-5386-2314-5
U6  - http://dx.doi.org/10.1109/RoboMech.2017.8261115
SP  - 7
EP  - 13
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  - 
TY  - CHAP
A1  - Steinbauer, Gerald
A1  - Ferrein, Alexander
T1  - CogRob 2018 : 
Cognitive Robotics Workshop.
Proceedings of the 11th Cognitive Robotics Workshop 2018
co-located with 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018).
Tempe, AZ, USA, October 27th, 2018.
T2  - CEUR workshop proceedings
Y1  - 2019
SN  - 1613-0073
N1  - edited by Gerald Steinbauer, Alexander Ferrein
IS  - Vol-2325
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  -