arXiv subjects

Tamás Haidegger

Publications and source records attributed to Tamás Haidegger.

5 recordsLinked to original sources

arXiv2026

Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medical robotics has been limited by a fundamental data problem: existing medical robotic datasets are small, single-embodiment, and rarely shared openly, restricting the development of foundation models that the field needs to advance. We introduce Open-H-Embodiment, the largest open dataset of medical robotic video with synchronized kinematics to date, spanning more than 50 institutions and multiple robotic platforms including the CMR Versius, Intuitive Surgical's da Vinci, da Vinci Research Kit (dVRK), Rob Surgical BiTrack, Virtual Incision's MIRA, Moon Surgical Maestro, and a variety of custom systems, spanning surgical manipulation, robotic ultrasound, and endoscopy procedures. We demonstrate the research enabled by this dataset through two foundation models. GR00T-H is the first open foundation vision-language-action model for medical robotics, which is the only evaluated model to achieve full end-to-end task completion on a structured suturing benchmark (25% of trials vs. 0% for all others) and achieves 64% average success across a 29-step ex vivo suturing sequence. We also train Cosmos-H-Surgical-Simulator, the first action-conditioned world model to enable multi-embodiment surgical simulation from a single checkpoint, spanning nine robotic platforms and supporting in silico policy evaluation and synthetic data generation for the medical domain. These results suggest that open, large-scale medical robot data collection can serve as critical infrastructure for the research community, enabling advances in robot learning, world modeling, and beyond.

cs.RO↗

arXiv2023

Evidence-based Hand Hygiene. Can You Trust the Fluorescent-based Assessment Methods?

Healthcare-Associated Infections present a major threat to patient safety globally. According to studies, more than 50% of HAI could be prevented by proper hand hygiene. Effectiveness of hand hygiene is regularly evaluated with the fluorescent method: performing hand hygiene with a handrub containing an ultra violet (UV) fluorescent marker. Typically, human experts evaluate the hands under UV-A light, and decide whether the applied handrub covered the whole hand surface. The aim of this study was to investigate how different experts judge the same UV-pattern, and compare that to microbiology for objective validation. Hands of volunteer participants were contaminated with high concentration of a Staphylococcus epidermidis suspension. Hands were incompletely disinfected with UV-labeled handrub. Four different UV-box type devices were used to take CCD pictures of the hands under UV light. Size of inadequately disinfected areas on the hands were determined in two different ways. First, based on microbiology; the areas where colonies were grown were measured. Second, four independent senior infection control specialists were asked to mark the missed areas on printed image, captured under UV light. 8 hands of healthy volunteers were examined. Expert evaluations were highly uncorrelated (regarding interrater reliability) and inconsistent. Microbiology results weakly correlated with the expert evaluations. In half of the cases, there were more than 10% difference in the size of properly disinfected area, as measured by microbiology versus human experts. Considering the result of the expert evaluations, variability was disconcertingly high. Evaluating the fluorescent method is challenging, even for highly experienced professionals. A patient safety quality assurance system cannot be built on these data quality.

cs.HC↗

arXiv2023

Image-Processing Based Methods to Improve the Robustness of Robotic Gripping

Image processing techniques have huge impact on most fields of robotics and industrial automation. Real time methods are usually employed in complex automation tasks, assisting with decision making or directly guiding robots and machinery, while post-processing is usually used for retrospective assessment of systems and processes. While artificial intelligence based image processing algorithms (usually neural networks) are more common nowadays, classical methods can also be used effectively even in modern applications. This paper focuses on optical flow based image processing, proving its efficiency by presenting optical flow based solutions for modern challenges in different fields of robotics such as robotic surgery and food industry automation. The main subject of the paper is a smart robotic gripper designed for automated robot cells in the meat industry, that is capable of slip detection and secure gripping of soft, slippery tissues with the help of the implemented optical flow based algorithm.

cs.RO↗

arXiv2023

Infrastructural Requirements and Regulatory Challenges of a Sustainable Urban Air Mobility Ecosystem

The United Nations has long put on the discussion agenda the sustainability challenges of ur- banization, which have both direct and indirect effects on future regulation strategies. Undoubtedly, most initiatives target better quality of life, improved access to services & goods and environment pro- tection. As commercial aerial urban transportation may become a feasible research goal in the near future, the connection possibilities between cities and regions scale up. It is expected that the growing number of vertical takeoff & landing vehicles used for passenger and goods transportation will change the infrastructure of the cities, and will have a significant effect on the cityscapes as well. In addition to the widely discussed regulatory and safety issues, the introduction of elevated traffic also raises environmental concerns, which influences the existing and required service and control infrastructure, and thus significantly affects sustainability. This paper provides narrated overview of the most common aspects of safety, licensing and regulations for passenger vertical takeoff & landing vehicles, and highlights the most important aspects of infrastructure planning, design and operation, which should be taken into account to maintain and efficiently operate this new way of transportation, leading to a sustainable urban air mobility ecosystem.

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arXiv2023

Establishing a Learning Model for Correct Hand Hygiene Technique in a NICU

The ability of healthcare workers to learn proper hand hygiene has been an understudied area of research. Generally, hand hygiene skills are regarded as a key contributor to reduce critical infections and healthcare-associated infections. In a clinical setup, at a Neonatal Intensive Care Unit (NICU), the outcome of a multi-modal training initiative was recorded, where objective feedback was provided to the staff. It was hypothesized that staff at the NICU are more sensitive towards applying increased patient safety measures. Outcomes were recorded as the ability to cover all hand surfaces with Alcohol-Based Handrub (ABHR), modelled as a time-series of measurements. The learning ability to rub in with 1.5 mL and with 3 mL was also assessed. As a secondary outcome, handrub consumption and infection numbers were recorded. It has been observed that some staff members were able to quickly learn the proper hand hygiene, even with the limited 1.5 mL, while others were not capable of acquiring the technique even with 3 mL. When analyzing the 1.5 mL group, it was deemed an insufficient ABHR amount, while with 3 mL, the critical necessity of skill training to achieve complete coverage was documented. Identifying these individuals helps the infection control staff to better focus their training efforts. The training led to a 157% increase in handrub consumption. The setting of the study did not allow to show a measurable reduction in the number of hospital infections. It has been concluded that the training method chosen by the staff greatly affects the quality of the outcomes.

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