arXiv subjects

Robert Schmitt

Publications and source records attributed to Robert Schmitt.

4 recordsLinked to original sources

arXiv2026

ROS 2-Based LiDAR Perception Framework for Mobile Robots in Dynamic Production Environments, Utilizing Synthetic Data Generation, Transformation-Equivariant 3D Detection and Multi-Object Tracking

Adaptive robots in dynamic production environments require robust perception capabilities, including 6D pose estimation and multi-object tracking. To address limitations in real-world data dependency, noise robustness, and spatiotemporal consistency, a LiDAR framework based on the Robot Operating System integrating a synthetic-data-trained Transformation-Equivariant 3D Detection with multi-object-tracking leveraging center poses is proposed. Validated across 72 scenarios with motion capture technology, overall results yield an Intersection over Union of 62.6% for standalone pose estimation, rising to 83.12% with multi-object-tracking integration. Our LiDAR-based framework achieves 91.12% of Higher Order Tracking Accuracy, advancing robustness and versatility of LiDAR-based perception systems for industrial mobile manipulators.

cs.RO↗

arXiv2026

Measurement-Based Validation of Geometry-Driven RIS Beam Steering in Industrial Environments

Reconfigurable intelligent surfaces (RISs) offer programmable control of radio propagation for future wireless systems. For configuration, geometry-driven analytical approaches are appealing for their simplicity and real-time operation, but their performance in challenging environments such as industrial halls with dense multipath and metallic scattering is not well established. To this end, we present a measurement-based evaluation of geometry-driven RIS beam steering in a large industrial hall using a 5 GHz RIS prototype. A novel RIS configuration is proposed in which four patch antennas are mounted in close proximity in front of the RIS to steer the incident field and enable controlled reflection. For this setup, analytically computed, quantized configurations are implemented. Two-dimensional received power maps from two measurement areas reveal consistent, spatially selective focusing. Configurations optimized near the receiver produce clear power maxima, while steering to offset locations triggers a rapid 20-30 dB reduction. With increasing RIS-receiver distance, elevation selectivity broadens due to finite-aperture and geometric constraints, while azimuth steering remains robust. These results confirm the practical viability of geometry-driven RIS beam steering in industrial environments and support its use for spatial field control and localization under non-ideal propagation.

eess.SP↗

arXiv2024

Infrared Beam-shaping on Demand via Tailored Geometric Phase Metasurfaces employing the Plasmonic Phase-Change Material In3SbTe2

Conventional optical elements are bulky and limited to specific functionalities, contradicting the increasing demand of miniaturization and multi-functionalities. Optical metasurfaces enable tailoring light-matter interaction at will, especially important for the infrared spectral range which lacks commercially available beam-shaping elements. While the fabrication of those metasurfaces usually requires cumbersome techniques, direct laser writing promises a simple and convenient alternative. Here, we exploit the non-volatile laser-induced insulator-to-metal transition of the plasmonic phase-change material In3SbTe2 (IST) for optical programming of large-area metasurfaces for infrared beam-shaping. We tailor the geometric phase of metasurfaces with rotated crystalline IST rod antennas to achieve beam steering, lensing, and beams carrying orbital angular momenta. Finally, we investigate multi-functional and cascaded metasurfaces exploiting enlarged holography, and design a single metasurface creating two different holograms along the optical axis. Our approach facilitates fabrication of large-area metasurfaces within hours, enabling rapid-prototyping of customized infrared meta-optics for sensing, imaging and quantum information.

physics.optics↗

arXiv2020

Leveraging Spatial Uncertainty for Online Error Compensation in EMT

Purpose: Electromagnetic Tracking (EMT) can potentially complement fluoroscopic navigation, reducing radiation exposure in a hybrid setting. Due to the susceptibility to external distortions, systematic error in EMT needs to be compensated algorithmically. Compensation algorithms for EMT in guidewire procedures are only practical in an online setting. Methods: We collect positional data and train a symmetric Artificial Neural Network (ANN) architecture for compensating navigation error. The results are evaluated in both online and offline scenarios and are compared to polynomial fits. We assess spatial uncertainty of the compensation proposed by the ANN. Simulations based on real data show how this uncertainty measure can be utilized to improve accuracy and limit radiation exposure in hybrid navigation. Results: ANNs compensate unseen distortions by more than 70%, outperforming polynomial regression. Working on known distortions, ANNs outperform polynomials as well. We empirically demonstrate a linear relationship between tracking accuracy and model uncertainty. The effectiveness of hybrid tracking is shown in a simulation experiment. Conclusion: ANNs are suitable for EMT error compensation and can generalize across unseen distortions. Model uncertainty needs to be assessed when spatial error compensation algorithms are developed, so that training data collection can be optimized. Finally, we find that error compensation in EMT reduces the need for x-ray images in hybrid navigation.

eess.IV↗