@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} } @article{FerreinSchifferLakemeyer2009, author = {Ferrein, Alexander and Schiffer, Stefan and Lakemeyer, Gerhard}, title = {Embedding fuzzy controllers in golog / Ferrein, Alexander ; Schiffer, Stefan ; Lakemeyer, Gerhard}, series = {IEEE International Conference on Fuzzy Systems, 2009. FUZZ-IEEE 2009}, journal = {IEEE International Conference on Fuzzy Systems, 2009. FUZZ-IEEE 2009}, publisher = {IEEE}, address = {New York}, isbn = {978-1-4244-3596-8}, pages = {894 -- 899}, year = {2009}, language = {en} } @article{NiemuellerFerreinBecketal.2010, author = {Niem{\"u}ller, Tim and Ferrein, Alexander and Beck, Daniel and Lakemeyer, Gerhard}, title = {Design Principles of the Component-Based Robot Software Framework Fawkes}, series = {Simulation, Modeling, and Programming for Autonomous Robots}, journal = {Simulation, Modeling, and Programming for Autonomous Robots}, pages = {300 -- 311}, year = {2010}, language = {en} } @article{SchifferFerrein2016, author = {Schiffer, Stefan and Ferrein, Alexander}, title = {Decision-Theoretic Planning with Fuzzy Notions in GOLOG}, series = {International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems}, volume = {24}, journal = {International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems}, number = {Issue Suppl. 2}, publisher = {World Scientific}, address = {Singapur}, issn = {1793-6411}, doi = {10.1142/S0218488516400134}, pages = {123 -- 143}, year = {2016}, abstract = {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.}, language = {en} } @article{FerreinJacobsLakemeyer2005, author = {Ferrein, Alexander and Jacobs, Stefan and Lakemeyer, Gerhard}, title = {Controlling Unreal Tournament 2004 Bots with the logic-based action language Golog / Jacobs, Stefan ; Ferrein, Alexander ; Lakemeyer, Gerhard}, series = {Proceedings of the First AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE).}, journal = {Proceedings of the First AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE).}, pages = {151 -- 152}, year = {2005}, language = {en} } @article{FerreinHermannsLakemeyer2006, author = {Ferrein, Alexander and Hermanns, Lutz and Lakemeyer, Gerhard}, title = {Comparing Sensor Fusion Techniques for Ball Position Estimation / Ferrein, Alexander ; Hermanns, Lutz ; Lakemeyer, Gerhard}, series = {RoboCup 2005: Robot Soccer World Cup IX}, journal = {RoboCup 2005: Robot Soccer World Cup IX}, publisher = {Springer}, address = {Berlin}, isbn = {978-3-540-35437-6}, pages = {154 -- 165}, year = {2006}, language = {en} } @article{ClaerFerreinSchiffer2019, author = {Claer, Mario and Ferrein, Alexander and Schiffer, Stefan}, title = {Calibration of a Rotating or Revolving Platform with a LiDAR Sensor}, series = {Applied Sciences}, volume = {Volume 9}, journal = {Applied Sciences}, number = {issue 11, 2238}, publisher = {MDPI}, address = {Basel}, issn = {2076-3417}, doi = {10.3390/app9112238}, pages = {18 Seiten}, year = {2019}, language = {en} } @article{SchifferFerreinLakemeyer2012, author = {Schiffer, Stefan and Ferrein, Alexander and Lakemeyer, Gerhard}, title = {Caesar: an intelligent domestic service robot}, series = {Intelligent service robotics}, volume = {5}, journal = {Intelligent service robotics}, number = {4}, publisher = {Springer}, address = {Berlin}, issn = {1861-2776}, doi = {10.1007/s11370-012-0118-y}, pages = {259 -- 276}, year = {2012}, abstract = {In this paper we present CAESAR, an intelligent domestic service robot. In domestic settings for service robots complex tasks have to be accomplished. Those tasks benefit from deliberation, from robust action execution and from flexible methods for human-robot interaction that account for qualitative notions used in natural language as well as human fallibility. Our robot CAESAR deploys AI techniques on several levels of its system architecture. On the low-level side, system modules for localization or navigation make, for instance, use of path-planning methods, heuristic search, and Bayesian filters. For face recognition and human-machine interaction, random trees and well-known methods from natural language processing are deployed. For deliberation, we use the robot programming and plan language READYLOG, which was developed for the high-level control of agents and robots; it allows combining programming the behaviour using planning to find a course of action. READYLOG is a variant of the robot programming language Golog. We extended READYLOG to be able to cope with qualitative notions of space frequently used by humans, such as "near" and "far". This facilitates human-robot interaction by bridging the gap between human natural language and the numerical values needed by the robot. Further, we use READYLOG to increase the flexible interpretation of human commands with decision-theoretic planning. We give an overview of the different methods deployed in CAESAR and show the applicability of a system equipped with these AI techniques in domestic service robotics}, 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} } @article{RensFerrein2013, author = {Rens, Gavin and Ferrein, Alexander}, title = {Belief-node condensation for online POMDP algorithms}, publisher = {IEEE}, address = {New York}, pages = {1 -- 7}, year = {2013}, abstract = {Slightly extended version of the paper accepted at the Robotics and Artificial Intelligence Workshop, a special track of IEEE AFRICON-2013, held in Mauritius, 9-12 September 2013}, language = {en} }