@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{HofmannMatareSchifferetal.2018, author = {Hofmann, Till and Matar{\´e}, Victor and Schiffer, Stefan and Ferrein, Alexander and Lakemeyer, Gerhard}, title = {Constraint-based online transformation of abstract plans into executable robot actions}, series = {Proceedings of the 2018 AAAI Spring Symposium on Integrating Representation, Reasoning, Learning, and Execution for Goal Directed Autonomy}, booktitle = {Proceedings of the 2018 AAAI Spring Symposium on Integrating Representation, Reasoning, Learning, and Execution for Goal Directed Autonomy}, pages = {549 -- 553}, year = {2018}, language = {en} } @inproceedings{FerreinSchifferKallweit2018, author = {Ferrein, Alexander and Schiffer, Stefan and Kallweit, Stephan}, title = {The ROSIN Education Concept - Fostering ROS Industrial-Related Robotics Education in Europe}, series = {ROBOT 2017: Third Iberian Robotics Conference}, booktitle = {ROBOT 2017: Third Iberian Robotics Conference}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-70836-2}, doi = {10.1007/978-3-319-70836-2_31}, pages = {370 -- 381}, year = {2018}, language = {en} } @inproceedings{HofmannMatareNeumannetal.2018, author = {Hofmann, Till and Matar{\´e}, Victor and Neumann, Tobias and Sch{\"o}nitz, Sebastian and Henke, Christoph and Limpert, Nicolas and Niemueller, Tim and Ferrein, Alexander and Jeschke, Sabina and Lakemeyer, Gerhard}, title = {Enhancing Software and Hardware Reliability for a Successful Participation in the RoboCup Logistics League 2017}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-00308-1}, doi = {10.1007/978-3-030-00308-1_40}, pages = {486 -- 497}, year = {2018}, language = {en} } @article{SchifferFerrein2018, author = {Schiffer, Stefan and Ferrein, Alexander}, title = {ERIKA—Early Robotics Introduction at Kindergarten Age}, series = {Multimodal Technologies Interact}, volume = {2}, journal = {Multimodal Technologies Interact}, number = {4}, publisher = {MDPI}, address = {Basel}, issn = {2414-4088}, doi = {10.3390/mti2040064}, pages = {15}, year = {2018}, abstract = {In this work, we report on our attempt to design and implement an early introduction to basic robotics principles for children at kindergarten age. One of the main challenges of this effort is to explain complex robotics contents in a way that pre-school children could follow the basic principles and ideas using examples from their world of experience. What sets apart our effort from other work is that part of the lecturing is actually done by a robot itself and that a quiz at the end of the lesson is done using robots as well. The humanoid robot Pepper from Softbank, which is a great platform for human-robot interaction experiments, was used to present a lecture on robotics by reading out the contents to the children making use of its speech synthesis capability. A quiz in a Runaround-game-show style after the lecture activated the children to recap the contents they acquired about how mobile robots work in principle. In this quiz, two LEGO Mindstorm EV3 robots were used to implement a strongly interactive scenario. Besides the thrill of being exposed to a mobile robot that would also react to the children, they were very excited and at the same time very concentrated. We got very positive feedback from the children as well as from their educators. To the best of our knowledge, this is one of only few attempts to use a robot like Pepper not as a tele-teaching tool, but as the teacher itself in order to engage pre-school children with complex robotics contents.}, language = {en} } @inproceedings{FerreinMeessenLimpertetal.2021, author = {Ferrein, Alexander and Meeßen, Marcus and Limpert, Nicolas and Schiffer, Stefan}, title = {Compiling ROS schooling curricula via contentual taxonomies}, series = {Robotics in Education}, booktitle = {Robotics in Education}, editor = {Lepuschitz, Wilfried}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-67411-3}, doi = {10.1007/978-3-030-67411-3_5}, pages = {49 -- 60}, year = {2021}, abstract = {The Robot Operating System (ROS) is the current de-facto standard in robot middlewares. The steadily increasing size of the user base results in a greater demand for training as well. User groups range from students in academia to industry professionals with a broad spectrum of developers in between. To deliver high quality training and education to any of these audiences, educators need to tailor individual curricula for any such training. In this paper, we present an approach to ease compiling curricula for ROS trainings based on a taxonomy of the teaching contents. The instructor can select a set of dedicated learning units and the system will automatically compile the teaching material based on the dependencies of the units selected and a set of parameters for a particular training. We walk through an example training to illustrate our work.}, language = {en} } @article{SchulteTiggesFoersterNikolovskietal.2022, author = {Schulte-Tigges, Joschua and F{\"o}rster, Marco and Nikolovski, Gjorgji and Reke, Michael and Ferrein, Alexander and Kaszner, Daniel and Matheis, Dominik and Walter, Thomas}, title = {Benchmarking of various LiDAR sensors for use in self-driving vehicles in real-world environments}, series = {Sensors}, volume = {22}, journal = {Sensors}, number = {19}, publisher = {MDPI}, address = {Basel}, issn = {1424-8220}, doi = {10.3390/s22197146}, pages = {20 Seiten}, year = {2022}, abstract = {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.}, 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 '21: Proceedings of the 14th Pervasive Technologies Related to Assistive Environments Conference}, booktitle = {PETRA '21: Proceedings of 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{ViehmannLimpertHofmannetal.2023, author = {Viehmann, Tarik and Limpert, Nicolas and Hofmann, Till and Henning, Mike and Ferrein, Alexander and Lakemeyer, Gerhard}, title = {Winning the RoboCup logistics league with visual servoing and centralized goal reasoning}, series = {RoboCup 2022: Robot World Cup XXV}, booktitle = {RoboCup 2022: Robot World Cup XXV}, editor = {Eguchi, Amy and Lau, Nuno and Paetzel-Pr{\"u}smann, Maike and Wanichanon, Thanapat}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-28468-7 (Print)}, doi = {https://doi.org/10.1007/978-3-031-28469-4_25}, pages = {300 -- 312}, year = {2023}, abstract = {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.}, 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{EichenbaumNikolovskiMuelhensetal.2023, author = {Eichenbaum, Julian and Nikolovski, Gjorgji and M{\"u}lhens, Leon and Reke, Michael and Ferrein, Alexander and Scholl, Ingrid}, title = {Towards a lifelong mapping approach using Lanelet 2 for autonomous open-pit mine operations}, series = {2023 IEEE 19th International Conference on Automation Science and Engineering (CASE)}, booktitle = {2023 IEEE 19th International Conference on Automation Science and Engineering (CASE)}, publisher = {IEEE}, isbn = {979-8-3503-2069-5 (Online)}, doi = {10.1109/CASE56687.2023.10260526}, pages = {8 Seiten}, year = {2023}, abstract = {Autonomous agents require rich environment models for fulfilling their missions. High-definition maps are a well-established map format which allows for representing semantic information besides the usual geometric information of the environment. These are, for instance, road shapes, road markings, traffic signs or barriers. The geometric resolution of HD maps can be as precise as of centimetre level. In this paper, we report on our approach of using HD maps as a map representation for autonomous load-haul-dump vehicles in open-pit mining operations. As the mine undergoes constant change, we also need to constantly update the map. Therefore, we follow a lifelong mapping approach for updating the HD maps based on camera-based object detection and GPS data. We show our mapping algorithm based on the Lanelet 2 map format and show our integration with the navigation stack of the Robot Operating System. We present experimental results on our lifelong mapping approach from a real open-pit mine.}, language = {en} } @inproceedings{NikolovskiLimpertNessauetal.2023, author = {Nikolovski, Gjorgji and Limpert, Nicolas and Nessau, Hendrik and Reke, Michael and Ferrein, Alexander}, title = {Model-predictive control with parallelised optimisation for the navigation of autonomous mining vehicles}, series = {2023 IEEE Intelligent Vehicles Symposium (IV)}, booktitle = {2023 IEEE Intelligent Vehicles Symposium (IV)}, publisher = {IEEE}, isbn = {979-8-3503-4691-6 (Online)}, doi = {10.1109/IV55152.2023.10186806}, pages = {6 Seiten}, year = {2023}, abstract = {The work in modern open-pit and underground mines requires the transportation of large amounts of resources between fixed points. The navigation to these fixed points is a repetitive task that can be automated. The challenge in automating the navigation of vehicles commonly used in mines is the systemic properties of such vehicles. Many mining vehicles, such as the one we have used in the research for this paper, use steering systems with an articulated joint bending the vehicle's drive axis to change its course and a hydraulic drive system to actuate axial drive components or the movements of tippers if available. To address the difficulties of controlling such a vehicle, we present a model-predictive approach for controlling the vehicle. While the control optimisation based on a parallel error minimisation of the predicted state has already been established in the past, we provide insight into the design and implementation of an MPC for an articulated mining vehicle and show the results of real-world experiments in an open-pit mine environment.}, language = {en} }