@inproceedings{AlhwarinFerreinGebhardtetal.2015, author = {Alhwarin, Faraj and Ferrein, Alexander and Gebhardt, Andreas and Kallweit, Stephan and Scholl, Ingrid and Tedjasukmana, Osmond Sanjaya}, title = {Improving additive manufacturing by image processing and robotic milling}, series = {2015 IEEE International Conference on Automation Science and Engineering (CASE), Aug 24-28, 2015 Gothenburg, Sweden}, booktitle = {2015 IEEE International Conference on Automation Science and Engineering (CASE), Aug 24-28, 2015 Gothenburg, Sweden}, doi = {10.1109/CoASE.2015.7294217}, pages = {924 -- 929}, year = {2015}, language = {en} } @inproceedings{AlhwarinFerreinScholl2018, author = {Alhwarin, Faraj and Ferrein, Alexander and Scholl, Ingrid}, title = {CRVM: Circular Random Variable-based Matcher - A Novel Hashing Method for Fast NN Search in High-dimensional Spaces}, series = {Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018}, booktitle = {Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018}, isbn = {978-989-758-276-9}, doi = {10.5220/0006692802140221}, pages = {214 -- 221}, year = {2018}, language = {en} } @inproceedings{AlhwarinFerreinScholl2019, author = {Alhwarin, Faraj and Ferrein, Alexander and Scholl, Ingrid}, title = {An Efficient Hashing Algorithm for NN Problem in HD Spaces}, series = {Lecture Notes in Computer Science}, booktitle = {Lecture Notes in Computer Science}, isbn = {978-303005498-4}, doi = {10.1007/978-3-030-05499-1_6}, pages = {101 -- 115}, year = {2019}, language = {en} } @inproceedings{AlhwarinSchifferFerreinetal.2018, author = {Alhwarin, Faraj and Schiffer, Stefan and Ferrein, Alexander and Scholl, Ingrid}, title = {Optimized KinectFusion Algorithm for 3D Scanning Applications}, series = {Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING}, booktitle = {Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING}, isbn = {978-989-758-278-3}, doi = {10.5220/0006594700500057}, pages = {50 -- 57}, year = {2018}, language = {en} } @inproceedings{AlhwarinSchifferFerreinetal.2019, author = {Alhwarin, Faraj and Schiffer, Stefan and Ferrein, Alexander and Scholl, Ingrid}, title = {An Optimized Method for 3D Body Scanning Applications Based on KinectFusion}, series = {Communications in Computer and Information Science}, volume = {1024}, booktitle = {Communications in Computer and Information Science}, publisher = {Springer}, issn = {1865-0929}, doi = {10.1007/978-3-030-29196-9_6}, pages = {100 -- 113}, year = {2019}, language = {en} } @inproceedings{ArndtConzenElsenetal.2023, author = {Arndt, Tobias and Conzen, Max and Elsen, Ingo and Ferrein, Alexander and Galla, Oskar and K{\"o}se, Hakan and Schiffer, Stefan and Tschesche, Matteo}, title = {Anomaly detection in the metal-textile industry for the reduction of the cognitive load of quality control workers}, series = {PETRA '23: Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments}, booktitle = {PETRA '23: Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments}, publisher = {ACM}, isbn = {9798400700699}, doi = {10.1145/3594806.3596558}, pages = {535 -- 542}, year = {2023}, abstract = {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.}, language = {en} } @inproceedings{BooysenMathewKnoxetal.2015, author = {Booysen, Tracy and Mathew, Thomas and Knox, Greig and Fong, W. K. and St{\"u}ttgen, Marcel and Ferrein, Alexander and Steinbauer, Gerald}, title = {The Scarab Project}, series = {ICRA 2015 Developing Countries Forum}, booktitle = {ICRA 2015 Developing Countries Forum}, pages = {3 S.}, year = {2015}, abstract = {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.}, language = {en} } @inproceedings{ChajanSchulteTiggesRekeetal.2021, author = {Chajan, Eduard and Schulte-Tigges, Joschua and Reke, Michael and Ferrein, Alexander and Matheis, Dominik and Walter, Thomas}, title = {GPU based model-predictive path control for self-driving vehicles}, series = {IEEE Intelligent Vehicles Symposium (IV)}, booktitle = {IEEE Intelligent Vehicles Symposium (IV)}, publisher = {IEEE}, isbn = {978-1-7281-5394-0}, doi = {10.1109/IV48863.2021.9575619}, pages = {1243 -- 1248}, year = {2021}, abstract = {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.}, language = {en} } @inproceedings{DeyElsenFerreinetal.2021, author = {Dey, Thomas and Elsen, Ingo and Ferrein, Alexander and Frauenrath, Tobias and Reke, Michael and Schiffer, Stefan}, title = {CO2 Meter: a do-it-yourself carbon dioxide measuring device for the classroom}, series = {PETRA 2021: The 14th PErvasive Technologies Related to Assistive Environments Conference}, booktitle = {PETRA 2021: The 14th PErvasive Technologies Related to Assistive Environments Conference}, editor = {Makedon, Fillia}, publisher = {Association for Computing Machinery}, address = {New York}, isbn = {9781450387927}, doi = {10.1145/3453892.3462697}, pages = {292 -- 299}, year = {2021}, abstract = {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.}, language = {en} } @inproceedings{DonnerRabelScholletal.2019, author = {Donner, Ralf and Rabel, Matthias and Scholl, Ingrid and Ferrein, Alexander and Donner, Marc and Geier, Andreas and John, Andr{\´e} and K{\"o}hler, Christian and Varga, Sebastian}, title = {Die Extraktion bergbaulich relevanter Merkmale aus 3D-Punktwolken eines untertagetauglichen mobilen Multisensorsystems}, series = {Tagungsband Geomonitoring}, booktitle = {Tagungsband Geomonitoring}, doi = {10.15488/4515}, pages = {91 -- 110}, year = {2019}, language = {de} }