TY - JOUR A1 - Schiffer, Stefan A1 - Ferrein, Alexander T1 - Decision-Theoretic Planning with Fuzzy Notions in GOLOG JF - International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems N2 - In this paper we present an extension of the action language Golog that allows for using fuzzy notions in non-deterministic argument choices and the reward function in decision-theoretic planning. Often, in decision-theoretic planning, it is cumbersome to specify the set of values to pick from in the non-deterministic-choice-of-argument statement. Also, even for domain experts, it is not always easy to specify a reward function. Instead of providing a finite domain for values in the non-deterministic-choice-of-argument statement in Golog, we now allow for stating the argument domain by simply providing a formula over linguistic terms and fuzzy uents. In Golog’s forward-search DT planning algorithm, these formulas are evaluated in order to find the agent’s optimal policy. We illustrate this in the Diner Domain where the agent needs to calculate the optimal serving order. Y1 - 2016 U6 - https://doi.org/10.1142/S0218488516400134 SN - 1793-6411 VL - 24 IS - Issue Suppl. 2 SP - 123 EP - 143 PB - World Scientific CY - Singapur ER - TY - CHAP A1 - Ferrein, Alexander A1 - Meeßen, Marcus A1 - Limpert, Nicolas A1 - Schiffer, Stefan ED - Lepuschitz, Wilfried T1 - Compiling ROS schooling curricula via contentual taxonomies T2 - Robotics in Education N2 - 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. Y1 - 2021 SN - 978-3-030-67411-3 U6 - https://doi.org/10.1007/978-3-030-67411-3_5 N1 - RiE: International Conference on Robotics in Education (RiE); Advances in Intelligent Systems and Computing book series (AISC, volume 1316) SP - 49 EP - 60 PB - Springer CY - Cham ER - TY - CHAP A1 - Hofmann, Till A1 - Mataré, Victor A1 - Schiffer, Stefan A1 - Ferrein, Alexander A1 - Lakemeyer, Gerhard T1 - Constraint-based online transformation of abstract plans into executable robot actions T2 - Proceedings of the 2018 AAAI Spring Symposium on Integrating Representation, Reasoning, Learning, and Execution for Goal Directed Autonomy Y1 - 2018 SP - 549 EP - 553 ER - TY - CHAP A1 - Ferrein, Alexander A1 - Niemüller, Tim A1 - Schiffer, Stefan A1 - Lakemeyer, Gerhard ED - Boots, Byron T1 - Lessons learnt from developing the embodied AI platform CAESAR for domestic service robotics T2 - Designing intelligent robots : reintegrating AI II ; papers from the AAAI spring symposium ; [held March 25 - 27, 2013 in Palo Alto, California, USA, on the campus of Stanford University]. (Technical Report / Association for the Advancement of Artificial Intelligence ; 2013,4) Y1 - 2013 SN - 9781577356011 SP - 21 EP - 26 ER - TY - CHAP A1 - Ferrein, Alexander A1 - Lakemeyer, Gerhard A1 - Schiffer, Stefan T1 - AllemaniACs@ home 2006 team description Y1 - 2006 SP - 1 EP - 6 ER - TY - JOUR A1 - Schiffer, Stefan A1 - Ferrein, Alexander T1 - ERIKA—Early Robotics Introduction at Kindergarten Age JF - Multimodal Technologies Interact N2 - 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. Y1 - 2018 U6 - https://doi.org/10.3390/mti2040064 SN - 2414-4088 VL - 2 IS - 4 PB - MDPI CY - Basel 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 - https://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 - 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 - https://doi.org/10.5220/0006594700500057 SP - 50 EP - 57 ER - TY - CHAP A1 - Ferrein, Alexander A1 - Schiffer, Stefan A1 - Kallweit, Stephan T1 - The ROSIN Education Concept - Fostering ROS Industrial-Related Robotics Education in Europe T2 - ROBOT 2017: Third Iberian Robotics Conference Y1 - 2018 SN - 978-3-319-70836-2 U6 - https://doi.org/10.1007/978-3-319-70836-2_31 N1 - Advances in Intelligent Systems and Computing, vol 694; (AISC, volume 694) SP - 370 EP - 381 PB - Springer CY - Cham ER - TY - CHAP A1 - Reke, Michael A1 - Peter, Daniel A1 - Schulte-Tigges, Joschua A1 - Schiffer, Stefan A1 - Ferrein, Alexander A1 - Walter, Thomas A1 - Matheis, Dominik T1 - A Self-Driving Car Architecture in ROS2 T2 - 2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa N2 - In this paper we report on an architecture for a self-driving car that is based on ROS2. Self-driving cars have to take decisions based on their sensory input in real-time, providing high reliability with a strong demand in functional safety. In principle, self-driving cars are robots. However, typical robot software, in general, and the previous version of the Robot Operating System (ROS), in particular, does not always meet these requirements. With the successor ROS2 the situation has changed and it might be considered as a solution for automated and autonomous driving. Existing robotic software based on ROS was not ready for safety critical applications like self-driving cars. We propose an architecture for using ROS2 for a self-driving car that enables safe and reliable real-time behaviour, but keeping the advantages of ROS such as a distributed architecture and standardised message types. First experiments with an automated real passenger car at lower and higher speed-levels show that our approach seems feasible for autonomous driving under the necessary real-time conditions. Y1 - 2020 SN - 978-1-7281-4162-6 U6 - https://doi.org/10.1109/SAUPEC/RobMech/PRASA48453.2020.9041020 N1 - 2020 International SAUPEC/RobMech/PRASA Conference, 29-31 Jan. 2020, Cape Town, South Africa SP - 1 EP - 6 PB - IEEE CY - New York, NY ER -