TY - JOUR A1 - Claer, Mario A1 - Ferrein, Alexander A1 - Schiffer, Stefan T1 - Calibration of a Rotating or Revolving Platform with a LiDAR Sensor JF - Applied Sciences Y1 - 2019 U6 - https://doi.org/10.3390/app9112238 SN - 2076-3417 VL - Volume 9 IS - issue 11, 2238 PB - MDPI CY - Basel ER - TY - CHAP A1 - Dey, Thomas A1 - Elsen, Ingo A1 - Ferrein, Alexander A1 - Frauenrath, Tobias A1 - Reke, Michael A1 - Schiffer, Stefan ED - Makedon, Fillia T1 - CO2 Meter: a do-it-yourself carbon dioxide measuring device for the classroom T2 - PETRA '21: Proceedings of the 14th Pervasive Technologies Related to Assistive Environments Conference N2 - 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. KW - embedded hardware KW - sensor networks KW - information systems KW - education KW - do-it-yourself Y1 - 2021 SN - 9781450387927 U6 - https://doi.org/10.1145/3453892.3462697 N1 - PETRA '21: The 14th PErvasive Technologies Related to Assistive Environments Conference Corfu Greece 29 June 2021- 2 July 2021 SP - 292 EP - 299 PB - Association for Computing Machinery CY - New York ER - TY - CHAP A1 - Chajan, Eduard A1 - Schulte-Tigges, Joschua A1 - Reke, Michael A1 - Ferrein, Alexander A1 - Matheis, Dominik A1 - Walter, Thomas T1 - GPU based model-predictive path control for self-driving vehicles T2 - IEEE Intelligent Vehicles Symposium (IV) N2 - 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. KW - Heuristic algorithms KW - Computational modeling KW - model-predictive control KW - GPU KW - autonomous driving Y1 - 2021 SN - 978-1-7281-5394-0 U6 - https://doi.org/10.1109/IV48863.2021.9575619 N1 - 2021 IEEE Intelligent Vehicles Symposium (IV), July 11-17, 2021. Nagoya, Japan SP - 1243 EP - 1248 PB - IEEE CY - New York, NY ER - 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 - Rens, Gavin A1 - Ferrein, Alexander A1 - Poel, Etienne van der T1 - Extending DTGolog to deal with POMD-Ps T2 - Proceedings of the Nineteenth Annual Symposium of the Pattern Recognition Association of South Africa (PRASA 2008) Y1 - 2008 SP - 49 EP - 54 ER - TY - JOUR A1 - Ferrein, Alexander A1 - Steinbauer, Gerald T1 - The Interplay of Aldebaran and RoboCup JF - KI - Künstliche Intelligenz Y1 - 2016 U6 - https://doi.org/10.1007/s13218-016-0440-1 SN - 1610-1987 VL - 30 IS - 3-4 SP - 325 EP - 326 PB - Springer CY - Berlin ER - TY - CHAP A1 - Viehmann, Tarik A1 - Limpert, Nicolas A1 - Hofmann, Till A1 - Henning, Mike A1 - Ferrein, Alexander A1 - Lakemeyer, Gerhard ED - Eguchi, Amy ED - Lau, Nuno ED - Paetzel-Prüsmann, Maike ED - Wanichanon, Thanapat T1 - Winning the RoboCup logistics league with visual servoing and centralized goal reasoning T2 - RoboCup 2022: Robot World Cup XXV N2 - 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. Y1 - 2023 SN - 978-3-031-28468-7 (Print) SN - 978-3-031-28469-4 (Online) U6 - https://doi.org/https://doi.org/10.1007/978-3-031-28469-4_25 N1 - Robot World Cup, RoboCup 2022. 17. July 2023. Bangkok, Thailand. Part of the Lecture Notes in Computer Science book series (LNAI,volume 13561) SP - 300 EP - 312 PB - Springer CY - Cham ER - TY - CHAP A1 - Niemueller, T. A1 - Lakemeyer, G. A1 - Reuter, S. A1 - Jeschke, S. A1 - Ferrein, Alexander T1 - Benchmarking of Cyber-Physical Systems in Industrial Robotics: The RoboCup Logistics League as a CPS Benchmark Blueprint T2 - Cyber-Physical Systems: Foundations, Principles and Applications N2 - In the future, we expect manufacturing companies to follow a new paradigm that mandates more automation and autonomy in production processes. Such smart factories will offer a variety of production technologies as services that can be combined ad hoc to produce a large number of different product types and variants cost-effectively even in small lot sizes. This is enabled by cyber-physical systems that feature flexible automated planning methods for production scheduling, execution control, and in-factory logistics. During development, testbeds are required to determine the applicability of integrated systems in such scenarios. Furthermore, benchmarks are needed to quantify and compare system performance in these industry-inspired scenarios at a comprehensible and manageable size which is, at the same time, complex enough to yield meaningful results. In this chapter, based on our experience in the RoboCup Logistics League (RCLL) as a specific example, we derive a generic blueprint for how a holistic benchmark can be developed, which combines a specific scenario with a set of key performance indicators as metrics to evaluate the overall integrated system and its components. KW - Smart factory KW - Industry 4.0 KW - Cyber-physical systems KW - Multi-robot systems KW - Autonomous mobile robots Y1 - 2017 U6 - https://doi.org/10.1016/B978-0-12-803801-7.00013-4 SP - 193 EP - 207 PB - Academic Press CY - London ER - TY - CHAP A1 - Rebel, Sören A1 - Hüning, Felix A1 - Scholl, Ingrid A1 - Ferrein, Alexander T1 - MQOne: Low-cost design for a rugged-terrain robot platform T2 - Intelligent robotics and applications : 8th International Conference, ICIRA 2015, Portsmouth, UK, August 24-27, 2015, Proceedings, Part II (Lecture notes in computer science : vol. 9245) N2 - Rugged terrain robot designs are important for field robotics missions. A number of commercial platforms are available, however, at an impressive price. In this paper, we describe the hardware and software component of a low-cost wheeled rugged-terrain robot. The robot is based on an electric children quad bike and is modified to be driven by wire. In terms of climbing properties, operation time and payload it can compete with some of the commercially available platforms, but at a far lower price. Y1 - 2015 SN - 978-3-319-22875-4 (print) ; 978-3-319-22876-1 (E-Book) U6 - https://doi.org/10.1007/978-3-319-22876-1_19 SP - 209 EP - 221 PB - Springer CY - Cham ER - TY - CHAP A1 - Nikolovski, Gjorgji A1 - Limpert, Nicolas A1 - Nessau, Hendrik A1 - Reke, Michael A1 - Ferrein, Alexander T1 - Model-predictive control with parallelised optimisation for the navigation of autonomous mining vehicles T2 - 2023 IEEE Intelligent Vehicles Symposium (IV) N2 - 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. KW - Mpc KW - Control KW - Path-following KW - Navigation KW - Automation Y1 - 2023 SN - 979-8-3503-4691-6 (Online) SN - 979-8-3503-4692-3 (Print) U6 - https://doi.org/10.1109/IV55152.2023.10186806 N1 - IEEE Symposium on Intelligent Vehicle, 4.-7. June 2023, Anchorage, AK, USA. PB - IEEE ER -