arXiv subjects

Sanghyun Kim

Publications and source records attributed to Sanghyun Kim.

At least 19 recordsLinked to original sources

arXiv2026

Projection-Retraction MPPI: Exact Constraint-Manifold Control for Manipulators

Model Predictive Path Integral (MPPI) control is widely used in manipulation for its gradient-free, parallel handling of non-convex costs. Manipulation tasks, however, often impose constraints that hold throughout the motion: a closed kinematic chain that two grasping arms keep exactly, or joint limits and obstacle clearances that are never crossed. MPPI handles such constraints only through the cost, as soft penalties that hold approximately and fail under a strong task cost. To address this, we propose Projection-Retraction MPPI (PR-MPPI), which enforces the constraints inside the sampled dynamics. At every rollout step, the sampled velocity is projected to satisfy both constraint types: the equality restricts it to a subspace, and each inequality to a half-space within that subspace, so inequality handling never breaks the equality. This projection, however, satisfies the constraints only to first order, and a finite step leaves a small drift off the equality. Therefore, we retract the returned command back onto the constraint to numerical tolerance and independent of task weighting. We validate PR-MPPI on 14-DoF dual-arm systems. In simulation, the returned commands satisfy the closed-chain equality to numerical tolerance through a joint-limit stress test and randomized obstacle avoidance. On real hardware, the arms of a Unitree H1-2 humanoid reactively avoid a moving obstacle. Code and experiment videos are available at https://rcilab.github.io/prmppi.

cs.RO↗

arXiv2026

GRACE: Gradient-Free Robot Action Generation via Combined Diffusion-MPPI Posterior Mean Estimation

Diffusion policies generate multimodal robot action sequences from demonstrations, but steering them toward deployment-time constraints typically relies on differentiable guidance costs. This excludes many practical safety constraints, such as binary collision checks, joint limits, and black-box rollout costs that are nondifferentiable. We propose Gradient-free Robot Action generation via Combined diffusion-MPPI posterior mean Estimation (GRACE), which guides a pretrained diffusion policy with Model Predictive Path Integral (MPPI) control using only forward cost evaluations. Building on the common score-ascent structure of diffusion and MPPI, GRACE constructs a cost-conditioned guidance posterior at each reverse step and estimates its mean with a single MPPI update centered at the diffusion reverse mean. For differentiable costs, GRACE recovers conventional gradient guidance under a first-order, matched-covariance approximation. GRACE attains higher success rates than diffusion-based and sampling-based baselines in simulation. On a real 7-DoF manipulator, GRACE avoids a deployment-time obstacle that the unguided prior collides with in every trial. Code and experiment videos are available at https://anonymous.4open.science/w/grace-70BB/.

cs.RO↗

arXiv2026

Instance-Enriched Semantic Maps for Visual Language Navigation

Visual Language Navigation (VLN) aims to enable an embodied agent to navigate complex environments by following natural language instructions. Recent approaches build semantic spatial maps and leverage Large Language Models (LLMs) for reasoning and decision making. Despite these advances, existing systems lack instance-level object detail and robustness to diverse user queries, limiting reliable navigation in complex indoor environments. To address these limitations, we propose Instance-Enriched Semantic Maps, a unified framework with three key contributions: (1) Instance-level two-and-a-half-dimensional (2.5D) rich information mapping that constructs maps from color and depth observations via open-vocabulary panoptic segmentation, preserving vertical distinctions and capturing small objects, while storing diverse semantic attributes and natural language captions enriched with room-level context. (2) Robust query processing via LLM-based target selection, which dynamically routes queries across type-specialized experts and integrates their outputs through score-level fusion, enabling consistent goal selection across diverse query formulations. (3) Storage-efficient semantic representation that achieves approximately 96% reduction compared to three-dimensional (3D) scene-graph approaches while preserving sufficient spatial information for navigation. The proposed 2.5D representation outperforms the 3D baseline by over 27% in prediction-normalized Area Under the Curve (AUC). In navigation experiments, our method achieves over 17% improvement in object retrieval and over 23% in navigation success compared to the baseline across diverse query types. The project page is available at https://rcilab.github.io/iesm_vln.

cs.RO↗

arXiv2026

Manifold-Constrained MPPI: Real-Time Sampling-Based Control Under Hard Constraints

Sampling-based model predictive control methods, such as Model Predictive Path Integral (MPPI), offer derivative-free optimization and robustness in complex robotic systems. However, standard MPPI relies on cost-based soft penalties that cannot guarantee hard-constraint satisfaction, severely limiting its applicability to highly constrained tasks such as closed-chain manipulation. To address this, we propose Manifold-Constrained MPPI (MC-MPPI), a real-time sampling-based control framework that enforces manifold-based equality constraints while preserving the computational advantages of MPPI. The key idea is to decouple the constrained optimal control problem into latent-space planning and execution-level correction. At the planning stage, a Variational Autoencoder (VAE) learns a low-dimensional latent representation of the constraint manifold, enabling MPPI to efficiently generate near-feasible candidate trajectories without per-sample modification. Since this reference enables accurate linearization of the equality constraints, an execution-level Quadratic Programming (QP) controller resolves the residual manifold mismatch in a single solve rather than through iterative projection. Experiments on a 14-DoF closed-chain dual-arm system in both simulation and real-world settings demonstrate that MC-MPPI operates stably at 100 Hz, reliably navigates dynamic environments while effectively maintaining hard equality constraints, and significantly outperforms baseline methods in tracking accuracy. Supplementary videos and implementation details are available at https://rcilab.github.io/mcmppi.

cs.RO↗

arXiv2026

Verification of the Polarimetric Capability of the East Asia VLBI Network

The East Asia VLBI Network (EAVN) has recently enabled dual-polarization observations at $22$ and $43\,\mathrm{GHz}$. We present the first systematic verification of its polarimetric performance using EAVN observations of M87, 3C 279, 3C 273, and OJ 287, calibrated with the GPCAL pipeline and evaluated against near-contemporaneous VLBA images at comparable frequencies. Most stations show stable polarimetric leakages with amplitudes of $5$-$10\%$ over monthly timescales. While several VERA stations exhibit D-term phase variations between epochs, we attribute these to field-rotator (FR) offsets and demonstrate that phase stability is restored after applying the analytically derived FR corrections. The resulting linear-polarization morphologies and EVPAs broadly agree with the VLBA results within uncertainties; fractional polarization measured by the EAVN tends to be slightly higher near polarization peaks. Although exact one-to-one comparisons are limited by moderate frequency and epoch differences, the combined evidence indicates robust EAVN polarimetric calibration and imaging capabilities at $22$ and $43\,\mathrm{GHz}$. These results support the scientific capability of EAVN polarimetry and lay the groundwork for expanded, higher-fidelity polarimetric studies in East Asia.

astro-ph.IM↗

arXiv2026

The IXPE and multifrequency polarimetric view of the extreme blazars 1ES 1101-232 and RGB J0710+591

Multiwavelength polarimetry is a powerful tool to probe magnetic field and flow geometries in the relativistic jets of blazars. In this respect, particularly interesting are the sources whose synchrotron emission covers a broad range of frequencies, from radio to X-rays, such as the BL Lac objects of the HSP type. Previous measurements including radio, optical and X-ray data show a clear trend, with the degree of polarization increasing with frequency. Here we report radio, optical and X-ray observations ($Swift$, $Nustar$ and $IXPE$) of 1ES 1101-232 and RGB J0710+591, two blazars belonging to the puzzling subclass of extreme BL Lacs (EHBL). For 1ES 1101-232 we found a strong frequency-dependency of the degree of polarization (with a ratio $Π_X/Π_O\simeq 5.2$). For RGB J0710+591, IXPE derived a 1$σ$ upper limit $Π_X<11.6\%$, comparable with the measured optical degree of polarization (average $Π_O\sim 12\%$). We discuss the results in the framework of current interpretations and, in particular, we report an improved version of the stratified shock model that is able to reproduce the observed data of both sources.

astro-ph.HE↗

arXiv2026

Where within the 3C 84 jet are $γ$-rays produced?

The location of $γ$-ray creation and emission within extra-galactic jets is a matter of active debate. One particularly well-suited source to pinpoint the location is the nearby, bright radio galaxy 3C 84, harbouring a powerful jet. Here we investigate the origin of $γ$-rays measured during a recent $γ$-ray flare, by analysing the linear polarisation signal of close-in-time very long baseline interferometry (VLBI) observations at centimetre and millimetre wavelengths. While 3C 84 is overall almost unpolarised, we find that close-in-time to the $γ$-ray flare peak regions at parsec-scale distances from the central engine shows a fractional linear polarisation increase. Under the physically well-motivated assumption of a causal relation between this polarisation enhancement and the $γ$-ray flare, and combined with insights from concurrent X-ray polarisation measurements, the $γ$-rays being created in this region is a physically motivated scenario, in a process consistent with synchrotron self-Compton.

astro-ph.HE↗

arXiv2026

Model Already Knows the Best Noise: Bayesian Active Noise Selection via Attention in Video Diffusion Model

The choice of initial noise strongly affects quality and prompt alignment in video diffusion; different seeds for the same prompt can yield drastically different results. While recent methods use externally designed priors (e.g., frequency filtering or inter-frame smoothing), they often overlook internal model signals that indicate inherently preferable seeds. To address this, we propose ANSE (Active Noise Selection for Generation), a model-aware framework that selects high-quality seeds by quantifying attention-based uncertainty. At its core is BANSA (Bayesian Active Noise Selection via Attention), an acquisition function that measures entropy disagreement across multiple stochastic attention samples to estimate model confidence and consistency. For efficient inference-time deployment, we introduce a Bernoulli-masked approximation of BANSA that estimates scores from a single diffusion step and a subset of informative attention layers. Experiments across diverse text-to-video backbones demonstrate improved video quality and temporal coherence with marginal inference overhead, providing a principled and generalizable approach to noise selection in video diffusion. See our project page: https://anse-project.github.io/anse-project/.

cs.CV↗

arXiv2026

Jet-torus interaction revealed by sub-parsec SO absorption in NGC 1052

We report the first λ2-mm very long baseline interferometry (VLBI) observations of the radio galaxy NGC 1052, conducted with the Korean VLBI Network (KVN) using a wide-band recording mode. Leveraging the wide bandwidth covering a velocity range at 2300 km/s, we successfully detect broad (> 700 km/s) multi-component SO J_N = 3_3 - 2_2 absorption against the sub-parsec-scale continuum structure. The absorption profile consists of both redshifted and blueshifted components, including a newly identified blueshifted feature at -412 km/s relative to the systemic velocity. Significant SO absorption is confined to the central components, with no substantial detection toward the outer jet components. This constrains the location of SO gas to a compact region smaller than 0.45 pc in the sub-parsec vicinity of the supermassive black hole (SMBH). Our results support the scenario in which SO molecules are evaporated through shock heating caused by jet-torus interaction. The SO gas clumps are likely driven outward by the jet, with some returning toward the SMBH as inflowing material. Comparison with 321 GHz H2O masers reveals partial similarities in spatial distribution and radial velocity, suggesting that the jet-torus interaction may also trigger the excitation of H2O masers.

astro-ph.GA↗

arXiv2026

Are diffusion models ready for materials discovery in unexplored chemical space?

While diffusion models are attracting increasing attention for the design of novel materials, their ability to generate low-energy structures in unexplored chemical spaces has not been systematically assessed. Here, we evaluate the performance of two diffusion models, MatterGen and DiffCSP, against three databases: a ternary oxide set (constructed by a genetic algorithm), a ternary nitride set (constructed by template informatics), and the GNoME database (constructed by a combination of both). We find that diffusion models generally perform stably in well-sampled chemical spaces (oxides and nitrides), but are less effective in uncommon ones (GNoME), which contains many compositions involving rare-earth elements and unconventional stoichiometry. Finally, we assess their size-extrapolation capability and observe a significant drop in performance when the number of atoms exceeds the trained range. This is attributed to the limitations imposed by periodic boundary conditions, which we refer to as the curse of periodicity. This study paves the way for future developments in materials design by highlighting both the strength and the limitations of diffusion models.

cond-mat.mtrl-sci↗

arXiv2026

Zonotope Shadow and Reflection Matching: A Novel GNSS Reflection-Based Framework for Enhanced Positioning Accuracy in Urban Areas

In urban areas, signal reception conditions are often poor due to reflections from buildings, resulting in inaccurate global navigation satellite system (GNSS)-based positioning. Various 3D-mapping-aided (3DMA) GNSS techniques, including shadow matching, have been proposed to address this issue. However, conventional shadow matching estimates positions in a discretized manner. The accuracy of this approach is limited by the resolution of the grid points representing the candidate receiver positions, making it difficult to achieve robust urban positioning and to ensure that the position estimate satisfies user-specified protection levels or safety bounds. To overcome these limitations, zonotope shadow matching (ZSM) has been proposed, which utilizes a set-based position estimate rather than grid-based estimates. ZSM calculates the GNSS shadow--an area on the ground where the line-of-sight (LOS) is blocked and only non-line-of-sight (NLOS) signals can be received--to estimate the receiver's position set. ZSM distinguishes between LOS and NLOS satellites, determining that the receiver is inside the GNSS shadow if the satellite is NLOS and outside if the satellite is LOS. However, relying solely on GNSS shadows limits the ability to sufficiently reduce the size of the receiver position set and to precisely estimate the receiver's location. To address this, we propose zonotope shadow and reflection matching (ZSRM) to enhance positioning accuracy in urban areas. The proposed ZSRM technique is validated through field tests using GNSS signals collected in an urban environment. Consequently, the RMS horizontal position error of ZSRM improved by 10.0% to 53.6% compared with ZSM, while the RMS cross-street and along-street position bounds improved by 18.0% to 50.1% and 30.7% to 59.3%, respectively.

eess.SP↗

arXiv2025

CUTE-Planner: Confidence-aware Uneven Terrain Exploration Planner

Planetary exploration robots must navigate uneven terrain while building reliable maps for space missions. However, most existing methods incorporate traversability constraints but may not handle high uncertainty in elevation estimates near complex features like craters, do not consider exploration strategies for uncertainty reduction, and typically fail to address how elevation uncertainty affects navigation safety and map quality. To address the problems, we propose a framework integrating safe path generation, adaptive confidence updates, and confidence-aware exploration strategies. Using Kalman-based elevation estimation, our approach generates terrain traversability and confidence scores, then incorporates them into Graph-Based exploration Planner (GBP) to prioritize exploration of traversable low-confidence regions. We evaluate our framework through simulated lunar experiments using a novel low-confidence region ratio metric, achieving 69% uncertainty reduction compared to baseline GBP. In terms of mission success rate, our method achieves 100% while baseline GBP achieves 0%, demonstrating improvements in exploration safety and map reliability.

cs.RO↗

arXiv2025

Detection of Compton scattering in the jet of 3C 84

3C 84 is the brightest cluster galaxy in the Perseus Cluster. It is among the closest radio-loud active galaxies and among the very few that can be detected from low frequency radio up to TeV $γ$-rays. Here we report on the first X-ray polarization observation of 3C~84 with the Imaging X-ray Polarimetry Explorer, for a total of 2.2 Msec that coincides with a flare in $γ$-rays. This is the longest observation for a radio-loud active galaxy that allowed us to reach unprecedented sensitivity, leading to the detection of an X-ray polarization degree of $\rmΠ_X=4.2\pm1.3\%$ ($\sim3.2σ$ confidence) at an X-ray electric vector polarization angle of $\rm ψ_X=163^{\circ}\pm9^{\circ}$, that is aligned with the radio jet direction on the sky. Optical polarization observations show fast variability about the jet axis as well. Our results strongly favor models in which X-rays are produced by Compton scattering from relativistic electrons -- specifically Synchrotron Self-Compton -- that takes places downstream, away from the supermassive black hole.

astro-ph.HE↗

arXiv2025

The variability angular diameter distance and the intrinsic brightness temperature of active galactic nuclei

Context. It has recently been suggested that angular diameter distances derived from comparing the variability timescales of blazars to angular size measurements with very long baseline interferometry (VLBI) may provide an alternative method to study the cosmological evolution of the Universe. Once the intrinsic brightness temperature ($T_{\rm int}$) is known, the angular diameter distance may be found without knowledge of the relativistic Doppler factor, opening up the possibility of a single rung distance measurement method from low $(z_{\rm cos}\ll1)$ to high $(z_{\rm cos}>4)$ redshifts. Aims. We aim to verify whether the variability-based estimates of the intrinsic brightness temperature of multiple active galactic nuclei (AGNs) converges to a common value. We also investigate whether the intrinsic brightness temperature changes as a function of frequency. Methods. We estimated the $T_{\rm int}$ of AGNs based on the flux variability of the radio cores of their jets. We utilized radio core light curves and size measurements of 75 sources at 15 GHz and of 37 sources at 43 GHz. We also derived $T_{\rm int}$ from a population study of the brightness temperatures of VLBI cores using VLBI survey data of more than $100$ sources at 24, 43, and 86 GHz. Results. Radio core variability-based estimates of $T_{\rm int}$ constrain upper limits of $\log_{10}T_{\rm int}$ [K]$<11.56$ at 15~GHz and $\log_{10}T_{\rm int}$ [K]$<11.65$ at 43 GHz under a certain set of geometric assumptions. The population analysis suggests lower limits of $\log_{10}T_{\rm int}$ [K]$>9.7$, $9.1$, and $9.3$ respectively at 24, 43, and 86 GHz. Even with monthly observations, variability-based estimates of $T_{\rm int}$ appear to be cadence-limited. Conclusions. Methods used to constrain $T_{\rm int}$ are more uncertain than previously thought. However, with improved datasets, the estimates should converge.

astro-ph.GA↗

arXiv2025

Few-Shot Pattern Detection via Template Matching and Regression

We address the problem of few-shot pattern detection, which aims to detect all instances of a given pattern, typically represented by a few exemplars, from an input image. Although similar problems have been studied in few-shot object counting and detection (FSCD), previous methods and their benchmarks have narrowed patterns of interest to object categories and often fail to localize non-object patterns. In this work, we propose a simple yet effective detector based on template matching and regression, dubbed TMR. While previous FSCD methods typically represent target exemplars as spatially collapsed prototypes and lose structural information, we revisit classic template matching and regression. It effectively preserves and leverages the spatial layout of exemplars through a minimalistic structure with a small number of learnable convolutional or projection layers on top of a frozen backbone We also introduce a new dataset, dubbed RPINE, which covers a wider range of patterns than existing object-centric datasets. Our method outperforms the state-of-the-art methods on the three benchmarks, RPINE, FSCD-147, and FSCD-LVIS, and demonstrates strong generalization in cross-dataset evaluation.

cs.CV↗

arXiv2025

Unveiling blazar synchrotron emission: a multiwavelength polarimetric study of HSP and LSP populations

Polarimetric properties of blazars allow us to put constraints on the acceleration mechanisms that fuel their powerful jets. By studying the multiwavelength polarimetric behaviour of high synchrotron peaked (HSP) and low synchrotron peaked (LSP) blazars, we aim to explore differences in their emission mechanisms and magnetic field structure in the acceleration region. In this study, we take advantage of several X-ray polarisation observations of HSP by the IXPE, including four new observations of Mrk 501, and optical polarisation observations of LSP from RoboPol and many others. We find that the polarisation degree (PD) distribution of HSP in X-rays is systematically higher than in optical and mm-radio wavelengths, as reported in previous IXPE publications. The distribution of the X-ray electric vector position angles (PA) is centered around the jet axis with most of the observations consistent with zero difference within uncertainties. In fact, the distribution of the offset of the PA from the jet axis is consistent between the LSP and HSP populations (with PA measured in optical for the first, X-ray for the latter), suggesting a common magnetic field structure close to the acceleration region, in strong support of the emerging energy stratified picture of particle acceleration followed by energy loss in blazar jets.

astro-ph.HE↗

arXiv2025

Enhancing Urban GNSS Positioning Reliability via Conservative Satellite Selection Using Unanimous Voting Across Multiple Machine Learning Classifiers

In urban environments, global navigation satellite system (GNSS) positioning is often compromised by signal blockages and multipath effects caused by buildings, leading to significant positioning errors. To address this issue, this study proposes a robust enhancement of zonotope shadow matching (ZSM)-based positioning by employing a conservative satellite selection strategy using unanimous voting across multiple machine learning classifiers. Three distinct models - random forest (RF), gradient boosting decision tree (GBDT), and support vector machine (SVM) - were trained to perform line-of-sight (LOS) and non-line-of-sight (NLOS) classification based on global positioning system (GPS) signal features. A satellite is selected for positioning only when all classifiers unanimously agree on its classification and their associated confidence scores exceed a threshold. Experiments with real-world GPS data collected in dense urban areas demonstrate that the proposed method significantly improves the positioning success rate and the receiver containment rate, even with imperfect LOS/NLOS classification. Although a slight increase in the position bound was observed due to the reduced number of satellites used, overall positioning reliability was substantially enhanced, indicating the effectiveness of the proposed approach in urban GNSS environments.

eess.SP↗

arXiv2025

CSC-MPPI: A Novel Constrained MPPI Framework with DBSCAN for Reliable Obstacle Avoidance

This paper proposes Constrained Sampling Cluster Model Predictive Path Integral (CSC-MPPI), a novel constrained formulation of MPPI designed to enhance trajectory optimization while enforcing strict constraints on system states and control inputs. Traditional MPPI, which relies on a probabilistic sampling process, often struggles with constraint satisfaction and generates suboptimal trajectories due to the weighted averaging of sampled trajectories. To address these limitations, the proposed framework integrates a primal-dual gradient-based approach and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to steer sampled input trajectories into feasible regions while mitigating risks associated with weighted averaging. First, to ensure that sampled trajectories remain within the feasible region, the primal-dual gradient method is applied to iteratively shift sampled inputs while enforcing state and control constraints. Then, DBSCAN groups the sampled trajectories, enabling the selection of representative control inputs within each cluster. Finally, among the representative control inputs, the one with the lowest cost is chosen as the optimal action. As a result, CSC-MPPI guarantees constraint satisfaction, improves trajectory selection, and enhances robustness in complex environments. Simulation and real-world experiments demonstrate that CSC-MPPI outperforms traditional MPPI in obstacle avoidance, achieving improved reliability and efficiency. The experimental videos are available at https://cscmppi.github.io

cs.RO↗