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 - http://dx.doi.org/10.1109/IV55152.2023.10186806 N1 - IEEE Symposium on Intelligent Vehicle, 4.-7. June 2023, Anchorage, AK, USA. PB - IEEE ER - TY - CHAP A1 - Eichenbaum, Julian A1 - Nikolovski, Gjorgji A1 - Mülhens, Leon A1 - Reke, Michael A1 - Ferrein, Alexander A1 - Scholl, Ingrid T1 - Towards a lifelong mapping approach using Lanelet 2 for autonomous open-pit mine operations T2 - 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE) N2 - 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. Y1 - 2023 SN - 979-8-3503-2069-5 (Online) SN - 979-8-3503-2070-1 (Print) U6 - http://dx.doi.org/10.1109/CASE56687.2023.10260526 N1 - 19th International Conference on Automation Science and Engineering (CASE), 26-30 August 2023, Auckland, New Zealand. PB - IEEE 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 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 - http://dx.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 - JOUR A1 - Schulte-Tigges, Joschua A1 - Förster, Marco A1 - Nikolovski, Gjorgji A1 - Reke, Michael A1 - Ferrein, Alexander A1 - Kaszner, Daniel A1 - Matheis, Dominik A1 - Walter, Thomas T1 - Benchmarking of various LiDAR sensors for use in self-driving vehicles in real-world environments JF - Sensors N2 - 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. KW - Lidar KW - Benchmark KW - Self-driving Y1 - 2022 U6 - http://dx.doi.org/10.3390/s22197146 SN - 1424-8220 N1 - This article belongs to the Special Issue "Sensor Fusion for Vehicles Navigation and Robotic Systems" VL - 22 IS - 19 PB - MDPI CY - Basel 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 - http://dx.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 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 Y1 - 2021 SN - 978-3-030-67411-3 U6 - http://dx.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 - 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 2021: 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 - http://dx.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 - Kirsch, Maximilian A1 - Mataré, Victor A1 - Ferrein, Alexander A1 - Schiffer, Stefan T1 - Integrating golog++ and ROS for Practical and Portable High-level Control T2 - 12th International Conference on Agents and Artificial Intelligence Y1 - 2020 U6 - http://dx.doi.org/10.5220/0008984406920699 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 Y1 - 2020 SN - 978-1-7281-4162-6 U6 - http://dx.doi.org/10.1109/SAUPEC/RobMech/PRASA48453.2020.9041020 SP - 1 EP - 6 ER - TY - CHAP A1 - Mataré, Victor A1 - Schiffer, Stefan A1 - Ferrein, Alexander ED - Steinbauer, Gerald ED - Ferrein, Alexander T1 - golog++ : An integrative system design T2 - 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 Y1 - 2019 SN - 1613-0073 SP - 29 EP - 35 ER - TY - CHAP A1 - Alhwarin, Faraj A1 - Ferrein, Alexander A1 - Scholl, Ingrid T1 - An Efficient Hashing Algorithm for NN Problem in HD Spaces T2 - Lecture Notes in Computer Science Y1 - 2019 SN - 978-303005498-4 U6 - http://dx.doi.org/10.1007/978-3-030-05499-1_6 N1 - 7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018; Funchal; Portugal; 16 January 2018 through 18 January 2018; Code 222779 SP - 101 EP - 115 ER - TY - CHAP A1 - Ferrein, Alexander A1 - Scholl, Ingrid A1 - Neumann, Tobias A1 - Krückel, Kai A1 - Schiffer, Stefan T1 - A system for continuous underground site mapping and exploration Y1 - 2019 U6 - http://dx.doi.org/10.5772/intechopen.85859 ER - TY - CHAP A1 - Ferrein, Alexander A1 - Bharatheesha, Mukunda A1 - Schiffer, Stefan A1 - Corbato, Carlos Hernandez T1 - 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 T2 - CEUR Workshop Proceedings Y1 - 2019 SN - 1613-0073 IS - Vol-2329 ER - 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 - http://dx.doi.org/10.3390/app9112238 SN - 2076-3417 VL - Volume 9 IS - issue 11, 2238 PB - MDPI CY - Basel ER - TY - CHAP A1 - Steinbauer, Gerald A1 - Ferrein, Alexander T1 - 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. T2 - CEUR workshop proceedings Y1 - 2019 SN - 1613-0073 N1 - edited by Gerald Steinbauer, Alexander Ferrein IS - Vol-2325 ER - TY - CHAP A1 - Hofmann, Till A1 - Limpert, Nicolas A1 - Mataré, Viktor A1 - Ferrein, Alexander A1 - Lakemeyer, Gerhard T1 - Winning the RoboCup Logistics League with Fast Navigation, Precise Manipulation, and Robust Goal Reasoning T2 - RoboCup 2019: Robot World Cup XXIII. RoboCup Y1 - 2019 SN - 978-3-030-35699-6 U6 - http://dx.doi.org/10.1007/978-3-030-35699-6_41 N1 - Lecture Notes in Computer Science, vol 11531 SP - 504 EP - 516 PB - Springer CY - Cham ER - TY - CHAP A1 - Niemueller, Tim A1 - Neumann, Tobias A1 - Henke, Christoph A1 - Schönitz, Sebastian A1 - Reuter, Sebastian A1 - Ferrein, Alexander A1 - Jeschke, Sabina A1 - Lakemeyer, Gerhard T1 - Improvements for a robust production in the RoboCup logistics league 2016 T2 - RoboCup 2016: Robot World Cup XX. RoboCup 2016. Y1 - 2017 SN - 978-3-319-68792-6 U6 - http://dx.doi.org/10.1007/978-3-319-68792-6_49 SP - 589 EP - 600 PB - Springer CY - Cham ER - TY - JOUR A1 - Niemueller, Tim A1 - Karras, Ulrich A1 - Ferrein, Alexander T1 - Meisterschaft der Maschinen: Die Industrial Logistic Liga JF - C´t Magazin für Computertechnik Y1 - 2017 IS - 26 ER - TY - CHAP A1 - Niemueller, Tim A1 - Zwilling, Frederik A1 - Lakemeyer, Gerhard A1 - Löbach, Matthias A1 - Reuter, Sebastian A1 - Jeschke, Sabina A1 - Ferrein, Alexander T1 - Cyber-Physical System Intelligence T2 - Industrial Internet of Things N2 - Cyber-physical systems are ever more common in manufacturing industries. Increasing their autonomy has been declared an explicit goal, for example, as part of the Industry 4.0 vision. To achieve this system intelligence, principled and software-driven methods are required to analyze sensing data, make goal-directed decisions, and eventually execute and monitor chosen tasks. In this chapter, we present a number of knowledge-based approaches to these problems and case studies with in-depth evaluation results of several different implementations for groups of autonomous mobile robots performing in-house logistics in a smart factory. We focus on knowledge-based systems because besides providing expressive languages and capable reasoning techniques, they also allow for explaining how a particular sequence of actions came about, for example, in the case of a failure. KW - Smart factory KW - Industry 4.0 KW - Multi-robot systems KW - Autonomous mobile robots KW - RoboCup Y1 - 2017 SN - 978-3-319-42559-7 U6 - http://dx.doi.org/10.1007/978-3-319-42559-7_17 N1 - Springer Series in Wireless Technology SP - 447 EP - 472 PB - Springer CY - Cham ER - TY - CHAP A1 - Stopforth, Riaan A1 - Davrajh, Shaniel A1 - Ferrein, Alexander T1 - South African robotics entity for a collaboration initiative T2 - Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference (PRASA-RobMech), 2016 Y1 - 2017 SN - 978-1-5090-3335-5 U6 - http://dx.doi.org/10.1109/RoboMech.2016.7813144 N1 - PRASA-RobMech, Nov. 30 2016-Dec. 2 2016, Stellenbosch, South Africa SP - 1 EP - 6 PB - IEEE ER -