TY - CHAP A1 - Upcroft, Ben A1 - Ridley, Matthew A1 - Ong, Lee Ling A1 - Douillard, Bertrand A1 - Kaupp, Tobias A1 - Kumar, Suresh A1 - Bailey, Tim A1 - Ramos, Fabio A1 - Makarenko, Alexei A1 - Brooks, Alex A1 - Sukkarieh, Salah A1 - Durrant-Whyte, Hugh F. T1 - Multilevel state estimation in an outdoor decentralised sensor network T2 - 10th International Symposium on Experimental Robotics 2006 (ISER'06), Rio de Janeiro, Brazil Y1 - 2006 ER - TY - CHAP A1 - Wang, X. Rosalind A1 - Kumar, Suresh A1 - Ramos, Fabio A1 - Kaupp, Tobias A1 - Upcroft, Ben A1 - Durrant-Whyte, Hugh F. T1 - Learning in hyperspectral images using a nonlinear dimensionality reduction technique T2 - 9th International Conference on Information Fusion (Fusion 2006), Florence, Italy Y1 - 2006 ER - TY - CHAP A1 - Brooks, Alex A1 - Makarenko, Alexei A1 - Kaupp, Tobias A1 - Williams, Stefan A1 - Durrant-Whyte, Hugh F. T1 - Implementation of an indoor active sensor network T2 - 9th International Symposium on Experimental Robotics 2004, Singapore Y1 - 2004 ER - TY - CHAP A1 - Reinhart, Lukas A1 - Endres, Felix A1 - Kaupp, Tobias A1 - Willert, Volker T1 - Augmented Virtuality zur Erkennung semi-künstlicher Bilddaten T2 - Poster Session des Forums Bildverarbeitung, 24. - 25. Nov. 2022, Karlsruhe Y1 - 2022 ER - TY - CHAP A1 - Kaupp, Tobias T1 - NEWHRI: Unifying characteristics of research in human-robot interaction T2 - NEWHRI workshop at ICRA'08 Y1 - 2008 UR - https://www.researchgate.net/profile/Xavier-Giralt/publication/232746634_Robot_Behaviour_Models_in_Human_Robot_Interaction/links/09e4150938e9d48d7b000000/Robot-Behaviour-Models-in-Human-Robot-Interaction.pdf ER - TY - CHAP A1 - Schirmer, Fabian A1 - Kranz, Philipp A1 - Manjunath, Meenakshi A1 - Jesus Raja, Jeshwitha A1 - Rose, Chad G. A1 - Kaupp, Tobias A1 - Daun, Marian T1 - Towards a conceptual safety planning framework for human-robot collaboration Y1 - 2023 UR - https://ceur-ws.org/Vol-3618/forum_paper_2.pdf PB - CEUR Workshop Proceedings ER - TY - JOUR A1 - Kranz, Philipp A1 - Schirmer, Fabian A1 - Kaupp, Tobias A1 - Daun, Marian T1 - Generative AI Copilot to Support Safety Analyses of Human–Robot Collaborations: Hazard Operability Analysis and GPT-4 JF - IEEE Software Y1 - 2024 U6 - https://doi.org/10.1109/MS.2024.3414445 SN - 0740-7459 VL - 41 IS - 6 SP - 65 EP - 72 PB - Institute of Electrical and Electronics Engineers (IEEE) ER - TY - CHAP A1 - Miller, Eddi A1 - Schmitt, Anna-Maria A1 - Kaupp, Tobias A1 - Batres, Rafael A1 - Schiffler, Andreas A1 - Schmitt, Jan T1 - A Peak Shaving Approach in Manufacturing Combining Machine Learning and Job Shop Scheduling T2 - Lecture Notes in Mechanical Engineering N2 - Computerized Numerical Control (CNC) plays an important role in highly autonomous manufacturing systems with multiple machine tools. The necessary Numerical Control (NC) programs to manufacture the parts are mostly written in standardized G-code. An a priori evaluation of the energy demand of CNC-based machine processes opens up the possibility of scheduling multiple jobs according to balanced energy consumption over a production period. Due to this, we present a combined Machine Learning (ML) and Job-Shop-Scheduling (JSS) approach to evaluate G-code for a CNC-milling process with respect to the energy demand of each G-command. The ML model training data are derived by the Latin hypercube sampling (LHS) method facing the main G-code operations G00, G01, and G02. The resulting energy demand for each job enhances a JSS algorithm to smooth the energy demand for multiple jobs, as peak power consumption needs to be avoided due to its expense. Y1 - 2025 SN - 9783031774287 U6 - https://doi.org/10.1007/978-3-031-77429-4_59 SN - 2195-4356 SP - 535 EP - 543 PB - Springer Nature Switzerland CY - Cham ER - TY - CHAP A1 - Miller, Eddi A1 - Schmitt, Anna-Maria A1 - Kaupp, Tobias A1 - Schiffler, Andreas A1 - Schmitt, Jan T1 - Deep Reinforcement Learning for Adaptive Job Shop Scheduling in Robotic Cells: Handling Disruptions Effectively T2 - 2025 11th International Conference on Mechatronics and Robotics Engineering (ICMRE) Y1 - 2025 UR - 10.1109/ICMRE64970.2025.10976238 ER - TY - JOUR A1 - Schirmer, Fabian A1 - Kranz, Philipp A1 - Rose, Chad G. A1 - Schmitt, Jan A1 - Kaupp, Tobias T1 - Towards Dynamic Human–Robot Collaboration: A Holistic Framework for Assembly Planning JF - Electronics N2 - The combination of human cognitive skills and dexterity with the endurance and repeatability of robots is a promising approach to modern assembly. However, efficiently allocating tasks and planning an assembly sequence between humans and robots is a manual, complex, and time-consuming activity. This work presents a framework named “Extract–Enrich–Assess–Plan–Review” that facilitates holistic planning of human–robot assembly processes. The framework automatically Extracts data from heterogeneous sources, Assesses the suitability of each assembly step to be performed by the human or robot, and Plans multiple assembly sequence plans (ASP) according to boundary conditions. Those sequences allow for a dynamic adaptation at runtime and incorporate different human–robot interaction modalities that are Synchronized, Cooperative, or Collaborative. An expert remains in the loop to Enrich the extracted data, and Review the results of the Assess and Plan steps with options to modify the process. To experimentally validate this framework, we compare the achieved degree of automation using three different CAD formats. We also demonstrate and analyze multiple assembly sequence plans that are generated by our system according to process time and the interaction modalities used. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-57825 SN - 2079-9292 VL - 14 IS - 1 PB - MDPI ER - TY - CHAP A1 - Spieß, Florian A1 - Friesslich, Jonas A1 - Bluemm, Daniel A1 - Mast, Fabio A1 - Vinokour, Dmitrij A1 - Kounev, Samuel A1 - Kaupp, Tobias A1 - Strobel, Norbert T1 - Towards a Mobile Robot Localization Benchmark with Challenging Sensordata in an Industrial Environment T2 - 2021 20th International Conference on Advanced Robotics (ICAR) N2 - To arrive at a realistic assessment of localization methods in terms of their performance in an industrial environment under various challenging conditions, we provide a benchmark to evaluate algorithms both for individual components as well as multi-sensor systems. For several sensor types, including wheel odometry, RGB cameras, RGB-D cameras, and LIDAR, potential issues were identified. The accuracy of wheel odometry, for example, when there are bumps on the track. For each sensor type, we explicitly chose a track for the benchmark dataset containing situations where the sensor fails to provide adequate measurements. Based on the acquired sensor data, localization can be achieved either using a single sensor information or sensor fusion. To help evaluate the output of associated localization algorithms, we provide a software to evaluate a set of metrics as part of the paper. An example application of the benchmark with state-of-the-art algorithms for each sensor is also provided. Y1 - 2021 U6 - https://doi.org/10.1109/ICAR53236.2021.9659355 SP - 857 EP - 864 ER - TY - JOUR A1 - Spiess, Florian A1 - Reinhart, Lukas A1 - Strobel, Norbert A1 - Kaupp, Tobias A1 - Kaiser, Dennis A1 - Kounev, Samuel T1 - People detection with depth silhouettes and convolutional neural networks on a mobile robot JF - Journal of Image and Graphics N2 - This paper presents a novel people detection approach for mobile robot applications based on a combination of classical computer vision techniques and a state-of-the-art neural network. Our approach involves an RGB-D camera as an environmental sensor. The depth data is used to extract silhouettes around people. The RGB images are subsequently augmented with this border information before passing it to the neural network. Under challenging lighting conditions, our system was able to outperform the neural network trained on regular RGB data alone by a factor of two. Y1 - 2021 UR - http://www.joig.net/index.php?m=content&c=index&a=show&catid=72&id=277 VL - 9 IS - 4 SP - 135 EP - 139 ER - TY - CHAP A1 - Spiess, Florian A1 - Strobel, Norbert A1 - Kaupp, Tobias A1 - Kounev, Samuel T1 - A data-driven Sensor Model for LIDAR Range Measurements used for Mobile Robot Navigation T2 - 2022 Sixth IEEE International Conference on Robotic Computing (IRC) N2 - In this paper, an analysis of the precision of LIDAR range measurements is presented. LIDAR data from two different sensors (HLS-LFCD-LDS and SICK TIM561) were analyzed regarding the influence of range, incident angle to the surface, and material. Based on the results, a data-driven model for LIDAR precision behavior was developed, and a comparison with standard deviation models based on the vendor-provided specifications was presented. Our model can be used to create realistic sensor simulations and to develop robot navigation algorithms weighing sensor range readings based on the precision. Y1 - 2022 U6 - https://doi.org/10.1109/IRC55401.2022.00020 SP - 76 EP - 80 ER - TY - JOUR A1 - Spiess, Florian A1 - Friesslich, Jonas A1 - Kaupp, Tobias A1 - Kounev, Samuel A1 - Strobel, Norbert T1 - Survey and Experimental Comparison of RGB-D Indoor Robot Navigation Methods Supported by ROS and Their Expansion via Fusion with Wheel Odometry and IMU Data JF - International Journal of Mechanical Engineering and Robotics Research Y1 - 2020 U6 - https://doi.org/10.18178/ijmerr.9.12.1532-1540 VL - 9 IS - 12 SP - 1532 EP - 1540 ER - TY - CHAP A1 - Schmitt, Jan A1 - Hillenbrand, Andreas A1 - Kranz, Philipp A1 - Kaupp, Tobias T1 - Assisted human-robot-interaction for industrial assembly: Application of spatial augmented reality (sar) for collaborative assembly tasks T2 - Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction Y1 - 2021 SP - 52 EP - 56 ER -