TY  - CHAP
A1  - Alhwarin, Faraj
A1  - Ferrein, Alexander
A1  - Gebhardt, Andreas
A1  - Kallweit, Stephan
A1  - Scholl, Ingrid
A1  - Tedjasukmana, Osmond Sanjaya
T1  - Improving additive manufacturing by image processing and robotic milling
T2  - 2015 IEEE International Conference on Automation Science and Engineering (CASE), Aug 24-28, 2015 Gothenburg, Sweden
Y1  - 2015
U6  - http://dx.doi.org/10.1109/CoASE.2015.7294217
SP  - 924
EP  - 929
ER  - 
TY  - CHAP
A1  - Alhwarin, Faraj
A1  - Ferrein, Alexander
A1  - Scholl, Ingrid
T1  - CRVM: Circular Random Variable-based Matcher - A Novel Hashing Method for Fast NN Search in High-dimensional Spaces
T2  - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018
Y1  - 2018
SN  - 978-989-758-276-9
U6  - http://dx.doi.org/10.5220/0006692802140221
SP  - 214
EP  - 221
ER  - 
TY  - CHAP
A1  - Alhwarin, Faraj
A1  - Ferrein, Alexander
A1  - Scholl, Ingrid
T1  - An Efficient Hashing Algorithm for NN Problem in HD Spaces
T2  - Lecture Notes in Computer Science
Y1  - 2019
SN  - 978-303005498-4
U6  - http://dx.doi.org/10.1007/978-3-030-05499-1_6
N1  - 7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018; Funchal; Portugal; 16 January 2018 through 18 January 2018; Code 222779
SP  - 101
EP  - 115
ER  - 
TY  - CHAP
A1  - Alhwarin, Faraj
A1  - Schiffer, Stefan
A1  - Ferrein, Alexander
A1  - Scholl, Ingrid
T1  - Optimized KinectFusion Algorithm for 3D Scanning Applications
T2  - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING
Y1  - 2018
SN  - 978-989-758-278-3
U6  - http://dx.doi.org/10.5220/0006594700500057
SP  - 50
EP  - 57
ER  - 
TY  - CHAP
A1  - Alhwarin, Faraj
A1  - Schiffer, Stefan
A1  - Ferrein, Alexander
A1  - Scholl, Ingrid
T1  - An Optimized Method for 3D Body Scanning Applications Based on KinectFusion
T2  - Communications in Computer and Information Science
Y1  - 2019
U6  - http://dx.doi.org/10.1007/978-3-030-29196-9_6
SN  - 1865-0929
N1  - 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018; Funchal; Portugal; 19 January 2018 through 21 January 2018
VL  - 1024
SP  - 100
EP  - 113
PB  - Springer
ER  - 
TY  - CHAP
A1  - Arndt, Tobias
A1  - Conzen, Max
A1  - Elsen, Ingo
A1  - Ferrein, Alexander
A1  - Galla, Oskar
A1  - Köse, Hakan
A1  - Schiffer, Stefan
A1  - Tschesche, Matteo
T1  - Anomaly detection in the metal-textile industry for the reduction of the cognitive load of quality control workers
T2  - PETRA '23: Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments
N2  - This paper presents an approach for reducing the cognitive load for humans working in quality control (QC) for production processes that adhere to the 6σ -methodology. While 100% QC requires every part to be inspected, this task can be reduced when a human-in-the-loop QC process gets supported by an anomaly detection system that only presents those parts for manual inspection that have a significant likelihood of being defective. This approach shows good results when applied to image-based QC for metal textile products.
KW  - Datasets
KW  - Neural networks
KW  - Anomaly detection
KW  - Quality control
KW  - Process optimization
Y1  - 2023
SN  - 9798400700699
U6  - http://dx.doi.org/10.1145/3594806.3596558
N1  - PETRA '23: Proceedings of the 16th International Conference on Pervasive Technologies Related to Assistive Environments, Corfu Greece, July 5 - 7, 2023.
SP  - 535
EP  - 542
PB  - ACM
ER  - 
TY  - CHAP
A1  - Booysen, Tracy
A1  - Mathew, Thomas
A1  - Knox, Greig
A1  - Fong, W. K.
A1  - Stüttgen, Marcel
A1  - Ferrein, Alexander
A1  - Steinbauer, Gerald
T1  - The Scarab Project
T2  - ICRA 2015 Developing Countries Forum
N2  - Urban Search and Rescue (USAR) is an active research
field in the robotics community. Despite recent advances
for many open research questions, these kind of systems are
not widely used in real rescue missions. One reason is that such
systems are complex and not (yet) very reliable; another is that
one has to be an robotic expert to run such a system. Moreover,
available rescue robots are very expensive and the benefits of
using them are still limited.
In this paper, we present the Scarab robot, an alternative
design for a USAR robot. The robot is light weight, humanpackable
and its primary purpose is that of extending the
rescuer’s capability to sense the disaster site. The idea is that a
responder throws the robot to a certain spot. The robot survives
the impact with the ground and relays sensor data such as
camera images or thermal images to the responder’s hand-held
control unit from which the robot can be remotely controlled.
Y1  - 2015
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  - http://dx.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
ER  - 
TY  - CHAP
A1  - Dey, Thomas
A1  - Elsen, Ingo
A1  - Ferrein, Alexander
A1  - Frauenrath, Tobias
A1  - Reke, Michael
A1  - Schiffer, Stefan
ED  - Makedon, Fillia
T1  - CO2 Meter: a do-it-yourself carbon dioxide measuring device for the classroom
T2  - PETRA 2021: The 14th PErvasive Technologies Related to Assistive Environments Conference
N2  - In this paper we report on CO2 Meter, a do-it-yourself carbon dioxide measuring device for the classroom. Part of the current measures for dealing with the SARS-CoV-2 pandemic is proper ventilation in indoor settings. This is especially important in schools with students coming back to the classroom even with high incidents rates. Static ventilation patterns do not consider the individual situation for a particular class. Influencing factors like the type of activity, the physical structure or the room occupancy are not incorporated. Also, existing devices are rather expensive and often provide only limited information and only locally without any networking. This leaves the potential of analysing the situation across different settings untapped. Carbon dioxide level can be used as an indicator of air quality, in general, and of aerosol load in particular. Since, according to the latest findings, SARS-CoV-2 can be transmitted primarily in the form of aerosols, carbon dioxide may be used as a proxy for the risk of a virus infection. Hence, schools could improve the indoor air quality and potentially reduce the infection risk if they actually had measuring devices available in the classroom. Our device supports schools in ventilation and it allows for collecting data over the Internet to enable a detailed data analysis and model generation. First deployments in schools at different levels were received very positively. A pilot installation with a larger data collection and analysis is underway.
KW  - embedded hardware
KW  - sensor networks
KW  - information systems
KW  - education
KW  - do-it-yourself
Y1  - 2021
SN  - 9781450387927
U6  - http://dx.doi.org/10.1145/3453892.3462697
N1  - PETRA '21: The 14th PErvasive Technologies Related to Assistive Environments Conference Corfu Greece 29 June 2021- 2 July 2021
SP  - 292
EP  - 299
PB  - Association for Computing Machinery
CY  - New York
ER  - 
TY  - CHAP
A1  - Donner, Ralf
A1  - Rabel, Matthias
A1  - Scholl, Ingrid
A1  - Ferrein, Alexander
A1  - Donner, Marc
A1  - Geier, Andreas
A1  - John, André
A1  - Köhler, Christian
A1  - Varga, Sebastian
T1  - Die Extraktion bergbaulich relevanter Merkmale aus 3D-Punktwolken eines untertagetauglichen mobilen Multisensorsystems
T2  - Tagungsband Geomonitoring
Y1  - 2019
U6  - http://dx.doi.org/10.15488/4515
SP  - 91
EP  - 110
ER  -