TY  - JOUR
A1  - Steinbauer, Gerald
A1  - Ferrein, Alexander
T1  - 20 Years of RoboCup
JF  - KI - Künstliche Intelligenz
Y1  - 2016
U6  - https://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  - JOUR
A1  - Ferrein, Alexander
A1  - Steinbauer, Gerald
T1  - Looking back on 20 Years of RoboCup
JF  - KI - Künstliche Intelligenz
Y1  - 2016
U6  - https://doi.org/10.1007/s13218-016-0443-y
SN  - 1610-1987
VL  - 30
IS  - 3-4
SP  - 321
EP  - 323
PB  - Springer
CY  - Berlin
ER  - 
TY  - CHAP
A1  - Marco, Heather G.
A1  - Ferrein, Alexander
T1  - AGNES: The African-German Network of Excellence in Science
T2  - Proceedings of the 2nd Developing World Robotics Forum, Workshop at IEEE AFRICON 2017
Y1  - 2017
SP  - 1
EP  - 2
ER  - 
TY  - CHAP
A1  - Schiffer, Stefan
A1  - Ferrein, Alexander
T1  - A System Layout for Cognitive Service Robots
T2  - Cognitive Robot Architectures. Proceedings of EUCognition 2016
Y1  - 2017
SN  - 1613-0073
N1  - CEUR-WS Vol-1855
SP  - 44
EP  - 45
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  - https://doi.org/10.1109/RoboMech.2017.8261115
SP  - 7
EP  - 13
ER  - 
TY  - CHAP
A1  - Ferrein, Alexander
A1  - Scholl, Ingrid
A1  - Neumann, Tobias
A1  - Krückel, Kai
A1  - Schiffer, Stefan
T1  - A system for continuous underground site mapping and exploration
Y1  - 2019
U6  - https://doi.org/10.5772/intechopen.85859
ER  - 
TY  - CHAP
A1  - Ferrein, Alexander
A1  - Bharatheesha, Mukunda
A1  - Schiffer, Stefan
A1  - Corbato, Carlos Hernandez
T1  - TRROS 2018 :  Teaching Robotics with ROS Workshop at ERF 2018;  Proceedings of the Workshop on Teaching Robotics with ROS (held at ERF 2018), co-located with European Robotics Forum 2018 (ERF 2018), Tampere, Finland, March 15th, 2018
T2  - CEUR Workshop Proceedings
Y1  - 2019
SN  - 1613-0073
IS  - Vol-2329
ER  - 
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  - https://doi.org/10.3390/app9112238
SN  - 2076-3417
VL  - Volume 9
IS  - issue 11, 2238
PB  - MDPI
CY  - Basel
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  - CHAP
A1  - Chajan, Eduard
A1  - Schulte-Tigges, Joschua
A1  - Reke, Michael
A1  - Ferrein, Alexander
A1  - Matheis, Dominik
A1  - Walter, Thomas
T1  - GPU based model-predictive path control for self-driving vehicles
T2  - IEEE Intelligent Vehicles Symposium (IV)
N2  - One central challenge for self-driving cars is a proper path-planning. Once a trajectory has been found, the next challenge is to accurately and safely follow the precalculated path. The model-predictive controller (MPC) is a common approach for the lateral control of autonomous vehicles. The MPC uses a vehicle dynamics model to predict the future states of the vehicle for a given prediction horizon. However, in order to achieve real-time path control, the computational load is usually large, which leads to short prediction horizons. To deal with the computational load, the control algorithm can be parallelized on the graphics processing unit (GPU). In contrast to the widely used stochastic methods, in this paper we propose a deterministic approach based on grid search. Our approach focuses on systematically discovering the search area with different levels of granularity. To achieve this, we split the optimization algorithm into multiple iterations. The best sequence of each iteration is then used as an initial solution to the next iteration. The granularity increases, resulting in smooth and predictable steering angle sequences. We present a novel GPU-based algorithm and show its accuracy and realtime abilities with a number of real-world experiments.
KW  - Heuristic algorithms
KW  - Computational modeling
KW  - model-predictive control
KW  - GPU
KW  - autonomous driving
Y1  - 2021
SN  - 978-1-7281-5394-0
U6  - https://doi.org/10.1109/IV48863.2021.9575619
N1  - 2021 IEEE Intelligent Vehicles Symposium (IV), July 11-17, 2021. Nagoya, Japan
SP  - 1243
EP  - 1248
PB  - IEEE
CY  - New York, NY
ER  -