Tonia Mielke, M.Sc.

@inproceedings{mielke_gesturing_2025,

title = {Gesturing Towards Efficient Robot Control: Exploring Sensor Placement and Control Modes for Mid-Air Human-Robot Interaction},

author = {T Mielke and F Heinrich and C Hansen},

doi = {10.1109/ICRA55743.2025.11127519},

year  = {2025},

date = {2025-09-02},

urldate = {2025-01-01},

booktitle = {2025 IEEE International Conference on Robotics and Automation (ICRA)},

abstract = {While collaborative robots effectively combine robotic precision with human capabilities, traditional control methods such as button presses or hand guidance can be slow and physically demanding. This has led to an increasing interest in natural user interfaces that integrate hand gesturebased interactions for more intuitive and flexible robot control. Therefore, this paper systematically explores mid-air robot control by comparing position and rate control modes with different state-of-the-art and novel sensor placements. A user study was conducted to evaluate each combination in terms of accuracy, task duration, perceived workload, and physical exertion. Our results indicate that position control is more efficient than rate control. Traditional desk-mounted sensors can provide a good balance between accuracy and comfort. However, robot-mounted sensors are a viable alternative for short-term, accurate control with less spatial requirements. Legmounted sensors, while comfortable, pose challenges to handeye coordination. Based on these findings, we provide design implications for improving the usability and comfort of midair human-robot interaction. Future research should extend this evaluation to a wider range of tasks and environments.},

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pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mielke_enhancing_2025,

title = {Enhancing AR-to-Robot Registration Accuracy: A Comparative Study of Marker Detection Algorithms and Registration Parameters},

author = {T Mielke and F Heinrich and C Hansen},

doi = {10.1109/ICRA55743.2025.11128039},

year  = {2025},

date = {2025-09-02},

urldate = {2025-09-02},

booktitle = {2025 IEEE International Conference on Robotics and Automation (ICRA)},

publisher = {IEEE},

abstract = {Augmented Reality (AR) offers potential for enhancing human-robot collaboration by enabling intuitive interaction and real-time feedback. A crucial aspect of AR-robot integration is accurate spatial registration to align virtual content with the physical robotic workspace. This paper systematically investigates the effects of different tracking techniques and registration parameters on AR-to-robot registration accuracy, focusing on paired-point methods. We evaluate four marker detection algorithms - ARToolkit, Vuforia, ArUco, and retroreflective tracking - analyzing the influence of viewing distance, angle, marker size, point distance, distribution, and quantity. Our results show that ARToolkit provides the highest registration accuracy. While larger markers and positioning registration point centroids close to target locations consistently improved accuracy, other factors such as point distance and quantity were highly dependent on the tracking techniques used. Additionally, we propose an effective refinement method using point cloud registration, significantly improving accuracy by integrating data from points recorded between registration locations. These findings offer practical guidelines for enhancing AR-robot registration, with future work needed to assess the transferability to other AR devices and robots.},

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pubstate = {published},

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}

@inproceedings{mielke_virtual_2025,

title = {Virtual Studies, Real Results? Assessing the Impact of Virtualization on Human-Robot Interaction},

author = {T Mielke and M Allgaier and D Schott and C Hansen and F Heinrich},

url = {https://dl.acm.org/doi/10.1145/3706599.3719724},

doi = {10.1145/3706599.3719724},

isbn = {979-8-4007-1395-8},

year  = {2025},

date = {2025-04-01},

urldate = {2025-04-01},

booktitle = {Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems},

pages = {1–8},

publisher = {ACM},

address = {Yokohama Japan},

abstract = {Extended Reality (XR) shows potential for human-centered evaluation of real-world scenarios and could improve efficiency and safety in robotic research. However, the validity of XR Human-Robot Interaction (HRI) studies remains underexplored. This paper investigates the transferability of HRI studies across virtualization levels for three tasks. Our results indicate XR study validity is task-specific, with task virtualization as a key influencing factor. Partially virtualized settings with virtual tasks and a real robot, as well as fully virtualized setups with a simulated robot, yielded results comparable to real setups for pick-and-place and robotic ultrasound. However, for precision-dependent peg-in-hole, differences were observed between real and virtualized conditions regarding completion time, perceived workload, and ease. Demonstrating the task dependency of XR transferability and comparing virtualization levels, our work takes an important step in assessing XR study validity. Future work should isolate factors affecting transferability and assess relative validity in the absence of absolute validity.},

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pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{schreiter_exploring_2025,

title = {Exploring Interaction Concepts for the Manipulation of a Collaborative Robot: A Comparative Study},

author = {J Schreiter and T Mielke and M Georgiades and M Pech and C Hansen and F Heinrich},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

booktitle = {Proceedings of the 2025 ACM/IEEE International Conference on Human-Robot Interaction},

pages = {55–64},

publisher = {IEEE Press},

address = {Melbourne, Australia},

series = {HRI '25},

abstract = {Robotic systems have the potential to enhance a wide range of domains, such as medical workflows, by automating individual steps of complex processes. However, human-robot interaction (HRI) is of critical importance, as effective collaboration between humans and robots is essential even in highly automated environments. Recent research has predominantly focused on the development of interaction methods rather than systematically comparing existing approaches. Therefore, we conducted a user study (n=20) to compare different HRI concepts for end effector manipulation combined with clutching mechanisms for manipulation activation in an alignment task using the example of robotic ultrasound (US). Manipulation methods included hand-guiding, teleoperation, and touchless interaction, while clutching mechanisms were realized through hand, voice, and foot interaction. The results indicate advantages of hand-guiding for manipulation. While no significant differences were observed between clutching mechanisms, strong evidence suggests comparable performance across these modalities. Notably, significant interaction effects on perceived workload reveal that the optimal clutching mechanism depends on the selected manipulation technique. This work underscores the critical importance of selecting appropriate HRI concepts and understanding the dependencies of manipulation techniques with clutching mechanisms. While our study included the usage of a robotic US, the insights gained are broadly transferable across various domains involving robotic manipulation tasks in human-robot collaboration.},

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pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mielke_interactive_2023,

title = {Interactive Registration Methods for Augmented Reality in Robotics: A Comparative Evaluation},

author = {T Mielke and F Joeres and D Schott and C Hansen},

url = {https://ieeexplore.ieee.org/document/10322246/},

doi = {10.1109/ISMAR-Adjunct60411.2023.00109},

isbn = {979-8-3503-2891-2},

year  = {2023},

date = {2023-10-01},

urldate = {2023-10-01},

booktitle = {2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)},

pages = {501–506},

publisher = {IEEE},

address = {Sydney, Australia},

abstract = {Augmented Reality (AR) visualization has shown potential for supporting intuitive and efficient human-robot interaction in a range of tasks. Since all these tasks are spatially related to the robot, the precise positioning of the AR content is critical to the applicability. However, most research has primarily focused on developing visualizations rather than exploring methods for aligning AR content in the robotic workspace. This paper aims to bridge this gap by implementing and comparing different interactive registration methods, including two point-based and one manual approach. We comparatively evaluated these registration methods in a user study (n=21), measuring registration accuracy, duration, and subjective user feedback. Our results indicate that the point-based methods outperform the manual approach in terms of both accuracy and perceived workload. Furthermore, participants achieved significantly faster performance with a point-based approach using physically defined registration points compared to a point-based approach using markers attached to the robot.},

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pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mielke_natural_2022,

title = {Natural 3D Object Manipulation for Interactive Laparoscopic Augmented Reality Registration},

author = {T Mielke and F Joeres and C Hansen},

editor = {Jessie Y. C. Chen and Gino Fragomeni},

doi = {10.1007/978-3-031-05939-1_21},

isbn = {978-3-031-05939-1},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {Virtual, Augmented and Mixed Reality: Design and Development},

pages = {317–328},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {Due to the growing focus on minimally invasive surgery, there is increasing interest in intraoperative software support. For example, augmented reality can be used to provide additional information. Accurate registration is required for effective support. In this work, we present a manual registration method that aims at mimicking natural manipulation of 3D objects using tracked surgical instruments. This method is compared to a point-based registration method in a simulated laparoscopic environment. Both registration methods serve as an initial alignment step prior to surface-based registration refinement. For the evaluation, we conducted a user study with 12 participants. The registration methods were compared in terms of registration accuracy, registration duration, and subjective usability feedback. No significant differences could be found with respect to the previously mentioned criteria between the manual and the point-based registration methods. Thus, the manual registration did not outperform the reference method. However, we found that our method offers qualitative advantages, which may make it more suitable for some application scenarios. Furthermore we identified possible approaches for improvement, which should be investigated in the future to strengthen possible advantages of our registration method.},

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pubstate = {published},

tppubtype = {inproceedings}

}