@inproceedings{MatareSchifferFerrein2019, author = {Matar{\´e}, Victor and Schiffer, Stefan and Ferrein, Alexander}, title = {golog++ : An integrative system design}, series = {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}, booktitle = {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}, editor = {Steinbauer, Gerald and Ferrein, Alexander}, issn = {1613-0073}, pages = {29 -- 35}, year = {2019}, 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{SchollBartellaMoluluoetal.2019, author = {Scholl, Ingrid and Bartella, Alex and Moluluo, Cem and Ertural, Berat and Laing, Frederic and Suder, Sebastian}, title = {MedicVR : Acceleration and Enhancement Techniques for Direct Volume Rendering in Virtual Reality}, series = {Bildverarbeitung f{\"u}r die Medizin 2019 : Algorithmen - Systeme - Anwendungen}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2019 : Algorithmen - Systeme - Anwendungen}, publisher = {Springer Vieweg}, address = {Wiesbaden}, isbn = {978-3-658-25326-4}, doi = {10.1007/978-3-658-25326-4_32}, pages = {152 -- 157}, year = {2019}, language = {en} } @inproceedings{WiesenEngemannLimpertetal.2018, author = {Wiesen, Patrick and Engemann, Heiko and Limpert, Nicolas and Kallweit, Stephan}, title = {Learning by Doing - Mobile Robotics in the FH Aachen ROS Summer School}, series = {European Robotics Forum 2018, TRROS18 Workshop}, booktitle = {European Robotics Forum 2018, TRROS18 Workshop}, pages = {47 -- 58}, year = {2018}, language = {en} } @inproceedings{FerreinSchollNeumannetal.2019, author = {Ferrein, Alexander and Scholl, Ingrid and Neumann, Tobias and Kr{\"u}ckel, Kai and Schiffer, Stefan}, title = {A system for continuous underground site mapping and exploration}, doi = {10.5772/intechopen.85859}, pages = {16 Seiten}, year = {2019}, language = {en} } @inproceedings{FerreinBharatheeshaSchifferetal.2019, author = {Ferrein, Alexander and Bharatheesha, Mukunda and Schiffer, Stefan and Corbato, Carlos Hernandez}, title = {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}, series = {CEUR Workshop Proceedings}, booktitle = {CEUR Workshop Proceedings}, number = {Vol-2329}, issn = {1613-0073}, pages = {68 Seiten}, year = {2019}, language = {en} } @inproceedings{SteinbauerFerrein2019, author = {Steinbauer, Gerald and Ferrein, Alexander}, title = {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.}, series = {CEUR workshop proceedings}, booktitle = {CEUR workshop proceedings}, number = {Vol-2325}, issn = {1613-0073}, pages = {46 Seiten}, year = {2019}, 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{UlmerBraunChengetal.2021, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Adapting Augmented Reality Systems to the users' needs using Gamification and error solving methods}, series = {Procedia CIRP}, volume = {104}, booktitle = {Procedia CIRP}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2212-8271}, doi = {10.1016/j.procir.2021.11.024}, pages = {140 -- 145}, year = {2021}, abstract = {Animations of virtual items in AR support systems are typically predefined and lack interactions with dynamic physical environments. AR applications rarely consider users' preferences and do not provide customized spontaneous support under unknown situations. This research focuses on developing adaptive, error-tolerant AR systems based on directed acyclic graphs and error resolving strategies. Using this approach, users will have more freedom of choice during AR supported work, which leads to more efficient workflows. Error correction methods based on CAD models and predefined process data create individual support possibilities. The framework is implemented in the Industry 4.0 model factory at FH Aachen.}, language = {en} } @inproceedings{ChavezBermudezWollert2022, author = {Chavez Bermudez, Victor Francisco and Wollert, J{\"o}rg}, title = {10BASE-T1L industry 4.0 smart switch for field devices based on IO-Link}, series = {2022 IEEE 18th International Conference on Factory Communication Systems (WFCS)}, booktitle = {2022 IEEE 18th International Conference on Factory Communication Systems (WFCS)}, publisher = {IEEE}, isbn = {978-1-6654-1086-1}, doi = {10.1109/WFCS53837.2022.9779176}, pages = {4 Seiten}, year = {2022}, abstract = {The recent amendment to the Ethernet physical layer known as the IEEE 802.3cg specification, allows to connect devices up to a distance of one kilometer and delivers a maximum of 60 watts of power over a twisted pair of wires. This new standard, also known as 10BASE-TIL, promises to overcome the limits of current physical layers used for field devices and bring them a step closer to Ethernet-based applications. The main advantage of 10BASE- TIL is that it can deliver power and data over the same line over a long distance, where traditional solutions (e.g., CAN, IO-Link, HART) fall short and cannot match its 10 Mbps bandwidth. Due to its recentness, IOBASE- TIL is still not integrated into field devices and it has been less than two years since silicon manufacturers released the first Ethernet-PHY chips. In this paper, we present a design proposal on how field devices could be integrated into a IOBASE-TIL smart switch that allows plug-and-play connectivity for sensors and actuators and is compliant with the Industry 4.0 vision. Instead of presenting a new field-level protocol for this work, we have decided to adopt the IO-Link specification which already includes a plug-and-play approach with features such as diagnosis and device configuration. The main objective of this work is to explore how field devices could be integrated into 10BASE-TIL Ethernet, its adaption with a well-known protocol, and its integration with Industry 4.0 technologies.}, language = {en} }