arXiv subjects

Seungwon Choi

Publications and source records attributed to Seungwon Choi.

14 recordsLinked to original sources

arXiv2026

SOLO: wide-field asteroid light curve monitoring system for SPHEREx

We present the Solar system Objects Light curve Observatory (SOLO), a wide-field, high-cadence optical survey system designed to obtain absolutely calibrated asteroid light curves, converted to the Gaia G-band photometric system, in support of the SPHEREx Solar System Object Catalog (SSOC). SOLO was installed at the Sierra Remote Observatories (SRO) in California, USA, in July 2025 and is optimized for continuous, multi-night monitoring of asteroid brightness variations. We describe the system configuration, remote operation, and data reduction pipeline, and evaluate its optical and photometric performance using commissioning data. SOLO achieves stable photometric calibration across the 11.6 deg^2 field of view and reaches a 10-sigma limiting magnitude of G ~ 17.5 for a 180 sec exposure. Sample asteroid light curves obtained over multiple nights demonstrate consistent absolute photometry at the same rotational phase, validating the estimated performance. Finally, we outline the planned operational use of SOLO in connection with NASA's SPHEREx mission. Full science operations of SOLO are scheduled to begin in January 2026. Using these data, we aim to obtain on the order of 10^3 absolutely calibrated asteroid light curves per year in the Gaia G-band, which will be used to support the construction and scientific utilization of the SPHEREx SSOC.

astro-ph.IM↗

arXiv2026

SQUIDPOL: Seoul National University QUadruple Imaging Device for POLarimetry

We present SQUIDPOL, a low-cost, multi-channel optical imaging polarimeter that performs simultaneous linear polarization measurements using a rotating half-wave plate, a non-polarizing beam splitter, and four wire-grid filters. We show that the off-the-shelf non-polarizing beam splitter introduces measurable polarization-dependent systematics, which can bias polarimetric measurements if left uncorrected. We quantify this effect for both transmitted and reflected beams and incorporate a correction scheme into the data-analysis pipeline. On-sky validation demonstrates stable and reproducible performance, achieving a polarization accuracy of about 0.15 percent for bright polarized standard stars. Mounted on the 60-cm Ritchey-Chretien telescope (focal length 4200 mm, f/7) at the Pyeongchang Observatory of Seoul National University, SQUIDPOL provides an effective common field of view of 13.5 by 8.2 arcminutes with a pixel scale of 0.45 arcseconds per pixel and supports standard B, V, R_C, and I_C filters.

astro-ph.IM↗

arXiv2026

Pedagogical Alignment for Vision-Language-Action Models: A Comprehensive Framework for Data, Architecture, and Evaluation in Education

Science demonstrations are important for effective STEM education, yet teachers face challenges in conducting them safely and consistently across multiple occasions, where robotics can be helpful. However, current Vision-Language-Action (VLA) models require substantial computational resources and sacrifice language generation capabilities to maximize efficiency, making them unsuitable for resource-constrained educational settings that require interpretable, explanation-generating systems. We present \textit{Pedagogical VLA Framework}, a framework that applies pedagogical alignment to lightweight VLA models through four components: text healing to restore language generation capabilities, large language model (LLM) distillation to transfer pedagogical knowledge, safety training for educational environments, and pedagogical evaluation adjusted to science education contexts. We evaluate Pedagogical VLA Framework across five science demonstrations spanning physics, chemistry, biology, and earth science, using an evaluation framework developed in collaboration with science education experts. Our evaluation assesses both task performance (success rate, protocol compliance, efficiency, safety) and pedagogical quality through teacher surveys and LLM-as-Judge assessment. We additionally provide qualitative analysis of generated texts. Experimental results demonstrate that Pedagogical VLA Framework achieves comparable task performance to baseline models while producing contextually appropriate educational explanations.

cs.CL↗

arXiv2026

Dust Properties of the Interstellar Object 3I/ATLAS Revealed by Optical and Near-Infrared Polarimetry

We present independent polarimetric observations of the interstellar object 3I/ATLAS, including the first near-infrared polarimetric measurements. Using imaging polarimeters, we measured the degree of linear polarization from the visible RC band (0.64 {\mu}m) to the near-infrared KS band (2.25 {\mu}m), and investigated its dependence on solar phase angle (polarization phase curve; PPC) and wavelength (polarization color curve; PCC). We confirm that the PPC of 3I/ATLAS differs significantly from those of typical Solar System comets, showing an unusually large polarization amplitude. This PPC shows no significant change in the RC band across perihelion passage, despite the perihelion lying within the water snow line. This indicates that the unusual polarimetric behavior of 3I/ATLAS is unlikely to be driven by transient volatile activity, but instead reflects intrinsic optical properties of refractory dust particles. The PCC increases with wavelength over 0.6-1.2 {\mu}m and peaks at 1.5-2.0 {\mu}m, suggesting that the dominant scattering units are dust aggregates composed of submicron-sized monomers, broadly consistent with interstellar dust and solar-system cometary aggregates. Taken together, our results indicate that 3I/ATLAS preserves polarimetric properties characteristic of a primitive cometary planetesimal formed in another planetary system, with a refractory dust composition that differs from that typically observed among Solar System comets, despite sharing a similar size scale of the aggregate building blocks.

astro-ph.EP↗

arXiv2025

Query-Calibrated Segmental Admission for Descriptor-Agnostic LiDAR Loop Closure in Repetitive Environments

Structurally repetitive environments produce visually plausible but aliased LiDAR loop candidates that can destabilize pose-graph optimization when admitted as loop factors. We propose Query-Calibrated Segmental Admission (QCSA), a descriptor-agnostic sparse loop-admission policy for graph-stability-oriented insertion. The policy scores short descriptor segments against hard negatives, calibrates which query-level segment hypotheses reach geometry, and inserts representative pairs validated by Generalized Iterative Closest Point (G-ICP). We evaluate it on the SNU Library Dataset (SNULib) and HeLiPR overlap routes. Aggregated over seven LiDAR descriptor families on SNULib, QCSA reduces inserted loop factors by 3.8 times, raises factor precision from 0.542 to 0.717, and sharply lowers false admissions per query group. With this sparser graph, it maintains comparable mean absolute trajectory error (ATE) and substantially reduces worst-sequence ATE versus dense Top1+G-ICP, from 1.064 to 0.778 m. The aggregate mean and worst-sequence ATE remain lower than the odometry-only reference. Under a matched factor budget, QCSA also attains lower trajectory error than SeqSLAM and sparse Top1+G-ICP selections. Fixed-transfer validation on HeLiPR, with no route-specific tuning, likewise suppresses hard-negative admissions. These results support the proposed admission layer for aliasing-heavy simultaneous localization and mapping (SLAM). Our implementation and dataset will be released at: https://github.com/wanderingcar/snu_library_dataset.

cs.RO↗

arXiv2025

SPHEREx Pre-Perihelion Mapping of $\mathrm{H_2O}$, $\mathrm{CO_2}$, and $\mathrm{CO}$ in Interstellar Object 3I/ATLAS

From 01- to 15-Aug-2025UT, the SPHEREx spacecraft observed interstellar object 3I/ATLAS. Using $R=40-130$ spectrophotometry at $\lambda=0.7-5$ $\mu$m, light curves, spectra, and imaging of ATLAS were obtained. From these, robust detections of water gas emission at $2.7-2.8$ $\mu$m and $CO_2$ gas at $4.23-4.27$ $\mu$m plus tentative detections of $^{13}CO_2$ and $CO$ gas were found. A slightly extended $H_2O$ coma was detected, and a huge $CO_2$ atmosphere of extending out to at least $4.2 \times 10^{5}$ km was discovered. Gas production rates and 1$\sigma$ errors for $H_2O$, $^{12}CO_2$, $^{13}CO_2$, and $CO$ were $Q_{gas} = 3.2 \times 10^{26} \pm 20\%$, $1.6 \times 10^{27} \pm 10\%$, $1.3 \times 10^{25} \pm 25\%$, and $1.0 \times 10^{26} \pm 25\%$, respectively. Co-addition of all $\lambda = 1.0-1.5$ $\mu$m scattered light continuum images from produced a high SNR image consistent with an unresolved source. The scattered light lightcurve showed $\lesssim 15\%$ variability over the observation period. The absolute brightness of ATLAS at $1.0-1.5$ $\mu$m is consistent with a $< 2.5$ km radius nucleus surrounded by a 100 times brighter coma. The $1.5-4.0$ $\mu$m continuum structure shows a strong feature commensurate with water ice absorption seen in KBOs and distant comets. The observed cometary behavior of ATLAS, including its preponderance of $CO_2$ emission, lack of $CO$ output, small size, and predominance of large icy chunks of material in a flux-dominant coma is similar to the behavior of short period comet 103P/Hartley 2, the ''hyperactive comet'' flyby target of the NASA Deep Impact extended mission in 2010. This correspondence suggests that ISOs can be significantly thermally processed before ejection into the ISM, and by comparison to 1I and 2I, can be widely variable in their physical outcome.

astro-ph.EP↗

arXiv2025

Surfel-LIO: Fast LiDAR-Inertial Odometry with Pre-computed Surfels and Hierarchical Z-order Voxel Hashing

LiDAR-inertial odometry (LIO) is an active research area, as it enables accurate real-time state estimation in GPS-denied environments. Recent advances in map data structures and spatial indexing have significantly improved the efficiency of LIO systems. Nevertheless, we observe that two aspects may still leave room for improvement: (1) nearest neighbor search often requires examining multiple spatial units to gather sufficient points for plane fitting, and (2) plane parameters are typically recomputed at every iteration despite unchanged map geometry. Motivated by these observations, we propose Surfel-LIO, which employs a hierarchical voxel structure (hVox) with pre-computed surfel representation. This design enables O(1) correspondence retrieval without runtime neighbor enumeration or plane fitting, combined with Z-order curve encoding for cache-friendly spatial indexing. Experimental results on the M3DGR dataset demonstrate that our method achieves significantly faster processing speed compared to recent state-of-the-art methods while maintaining comparable state estimation accuracy. Our implementation is publicly available at https://github.com/93won/lidar_inertial_odometry.

cs.RO↗

arXiv2025

Statistical Uncertainty Learning for Robust Visual-Inertial State Estimation

A fundamental challenge in robust visual-inertial odometry (VIO) is to dynamically assess the reliability of sensor measurements. This assessment is crucial for properly weighting the contribution of each measurement to the state estimate. Conventional methods often simplify this by assuming a static, uniform uncertainty for all measurements. This heuristic, however, may be limited in its ability to capture the dynamic error characteristics inherent in real-world data. To improve this limitation, we present a statistical framework that learns measurement reliability assessment online, directly from sensor data and optimization results. Our approach leverages multi-view geometric consistency as a form of self-supervision. This enables the system to infer landmark uncertainty and adaptively weight visual measurements during optimization. We evaluated our method on the public EuRoC dataset, demonstrating improvements in tracking accuracy with average reductions of approximately 24\% in translation error and 42\% in rotation error compared to baseline methods with fixed uncertainty parameters. The resulting framework operates in real time while showing enhanced accuracy and robustness. To facilitate reproducibility and encourage further research, the source code will be made publicly available.

cs.RO↗

arXiv2025

GUARD: Toward a Compromise between Traditional Control and Learning for Safe Robot Systems

This paper presents the framework \textbf{GUARD} (\textbf{G}uided robot control via \textbf{U}ncertainty attribution and prob\textbf{A}bilistic kernel optimization for \textbf{R}isk-aware \textbf{D}ecision making) that combines traditional control with an uncertainty-aware perception technique using active learning with real-time capability for safe robot collision avoidance. By doing so, this manuscript addresses the central challenge in robotics of finding a reasonable compromise between traditional methods and learning algorithms to foster the development of safe, yet efficient and flexible applications. By unifying a reactive model predictive countouring control (RMPCC) with an Iterative Closest Point (ICP) algorithm that enables the attribution of uncertainty sources online using active learning with real-time capability via a probabilistic kernel optimization technique, \emph{GUARD} inherently handles the existing ambiguity of the term \textit{safety} that exists in robotics literature. Experimental studies indicate the high performance of \emph{GUARD}, thereby highlighting the relevance and need to broaden its applicability in future.

cs.RO↗

arXiv2025

Optical and Near-Infrared Contemporaneous Polarimetry of C/2023 A3 (Tsuchinshan-ATLAS)

We conducted contemporaneous optical and near-infrared polarimetric and spectroscopic observations of C/2023 A3 (Tsuchinshan-ATLAS, hereafter T-A) from 2024 October 16 to December 17, covering a wide range of phase angles (20-123 deg) and wavelength (0.5-2.3 um). We paid special attention to gas contamination in the dust polarization using these data. As a result, we find the maximum polarization degree $P_max=31.21 +- 0.05 %, 33.52 +- 0.06 %, 35.12 +- 0.01 %, 37.57 +- 0.01 %, and 35.35 +- 0.01 % in the Rc-, Ic-, J-, H-, and Ks-bands, respectively. Although dust polarization shows a red slope at shorter wavelengths and can peak around 1.6 um, the phase angle at which maximum polarization occurs exhibits less dependence on wavelength (alpha_max ~ 90 deg - 95 deg). Although only a few historically bright comets, such as West, Halley, and Hale-Bopp, have undergone such extensive dust-polarization observations, our measurements are generally consistent with those of two comets that possibly originated from the Oort Cloud (West and Halley). From these results, we conjecture that the optical properties and growth processes of dust in the presolar nebula, which formed these cometary nuclei, were likely uniform.

astro-ph.EP↗

arXiv2024

A Practical Gated Recurrent Transformer Network Incorporating Multiple Fusions for Video Denoising

State-of-the-art (SOTA) video denoising methods employ multi-frame simultaneous denoising mechanisms, resulting in significant delays (e.g., 16 frames), making them impractical for real-time cameras. To overcome this limitation, we propose a multi-fusion gated recurrent Transformer network (GRTN) that achieves SOTA denoising performance with only a single-frame delay. Specifically, the spatial denoising module extracts features from the current frame, while the reset gate selects relevant information from the previous frame and fuses it with current frame features via the temporal denoising module. The update gate then further blends this result with the previous frame features, and the reconstruction module integrates it with the current frame. To robustly compute attention for noisy features, we propose a residual simplified Swin Transformer with Euclidean distance (RSSTE) in the spatial and temporal denoising modules. Comparative objective and subjective results show that our GRTN achieves denoising performance comparable to SOTA multi-frame delay networks, with only a single-frame delay.

cs.CV↗

arXiv2023

Efficient Graduated Non-Convexity for Pose Graph Optimization

We propose a novel approach to Graduated Non-Convexity (GNC) and demonstrate its efficacy through its application in robust pose graph optimization, a key component in SLAM backends. Traditional GNC methods often rely on heuristic methods for GNC schedule, updating control parameter μ for escalating the non-convexity. In contrast, our approach leverages the properties of convex functions and convex optimization to identify the boundary points beyond which convexity is no longer guaranteed, thereby eliminating redundant optimization steps in existing methodologies and enhancing both speed and robustness. We show that our method outperforms the state-of-the-art method in terms of speed and accuracy when used for robust back-end pose graph optimization via GNC. Our work builds upon and enhances the open-source riSAM framework. Our implementation can be accessed from: https://github.com/SNU-DLLAB/EGNC-PGO

cs.RO↗

arXiv2023

Adaptive Graduated Non-Convexity for Pose Graph Optimization

We present a novel approach to robust pose graph optimization based on Graduated Non-Convexity (GNC). Unlike traditional GNC-based methods, the proposed approach employs an adaptive shape function using B-spline to optimize the shape of the robust kernel. This aims to reduce GNC iterations, boosting computational speed without compromising accuracy. When integrated with the open-source riSAM algorithm, the method demonstrates enhanced efficiency across diverse datasets. Accompanying open-source code aims to encourage further research in this area. https://github.com/SNU-DLLAB/AGNC-PGO

cs.RO↗

arXiv2022

Gated Recurrent Unit for Video Denoising

Current video denoising methods perform temporal fusion by designing convolutional neural networks (CNN) or combine spatial denoising with temporal fusion into basic recurrent neural networks (RNNs). However, there have not yet been works which adapt gated recurrent unit (GRU) mechanisms for video denoising. In this letter, we propose a new video denoising model based on GRU, namely GRU-VD. First, the reset gate is employed to mark the content related to the current frame in the previous frame output. Then the hidden activation works as an initial spatial-temporal denoising with the help from the marked relevant content. Finally, the update gate recursively fuses the initial denoised result with previous frame output to further increase accuracy. To handle various light conditions adaptively, the noise standard deviation of the current frame is also fed to these three modules. A weighted loss is adopted to regulate initial denoising and final fusion at the same time. The experimental results show that the GRU-VD network not only can achieve better quality than state of the arts objectively and subjectively, but also can obtain satisfied subjective quality on real video.

cs.CV↗