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Related Articles from SNS
ExpertGen: Scalable Sim-to-Real Expert Policy Learning from Imperfect Behavior Priors
arXiv:2603.15956v3 Announce Type: replace Abstract: Learning generalizable and robust behavior cloning policies requires large volumes of high-quality robotics data. While human demonstrations (e.g., through teleoperation) serve as the standard source for expert behaviors, acquiring such data at scale in the real world is prohibitively expensive. This paper introduces ExpertGen, a framework that automates expert policy learning in simulation to enable scalable sim-to-real transfer.
NVIDIA Isaac Sim: Enabling Scalable, GPU-Accelerated Simulation for Robotics
Announce Type: new Abstract: Simulation has become a core infrastructure for robotics research. Unlike previous simulators, NVIDIA Isaac Sim leverages GPU acceleration to enable large-scale parallel training and physics-accurate modeling. Its synthetic data generation pipeline alleviates the scarcity of high-quality training data, supporting data-driven robot learning and large-scale simulation-centric experimentation.
VIRTUS-FPP: Virtual Sensor Modeling for Fringe Projection Profilometry in NVIDIA Isaac Sim
Announce Type: replace-cross Abstract: Fringe projection profilometry (FPP) is a high-precision structured-light sensing technique for 3D surface reconstruction, yet its practical deployment is often constrained by complex calibration procedures, sensitivity to environmental conditions, and the high cost of physical experimentation. At the same time, robotics research increasingly relies on simulation platforms such as NVIDIA Isaac Sim for scalable development and validation, but accurate...
Compile to Compress: Boosting Formal Theorem Provers by Compiler Outputs
arXiv:2604.18587v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated significant potential in formal theorem proving, yet state-of-the-art performance often necessitates prohibitive test-time compute via massive roll-outs or extended context windows. In this work, we address this scalability bottleneck by exploiting an informative structure in formal verification: the observation that compilers map a vast space of diverse proof attempts to a compact set of...
Beyond Imitation: Reinforcement Learning-Based Sim-Real Co-Training for VLA Models
arXiv:2602.12628v4 Announce Type: replace Abstract: Simulation offers a scalable and low-cost way to enrich vision-language-action (VLA) training, reducing reliance on expensive real-robot demonstrations. However, most sim-real co-training methods rely on supervised fine-tuning (SFT), which treats simulation as a static source of demonstrations and does not exploit large-scale closed-loop interaction. Consequently, real-world gains and generalization are often limited.
DTCO of NOR-Type IGZO FeFETs for 3D Heterogeneous AI Memories: A Read-Centric Perspective
arXiv:2604.13624v2 Announce Type: replace Abstract: InGaZnO (IGZO)-channel FeFETs have attracted notable interest thanks to recent advances in endurance, opening up their application space for read-dominated AI memory tiers. This work evaluates the viability of NOR-type IGZO FeFETs for 3D heterogeneous AI memories from a read-centric design-technology co-optimization (DTCO) perspective, spanning on-chip back-end-of-line (BEOL) RAMs and hybrid-bonded memory chiplets, and off-chip,...
A Simulation Platform for Flapping-Wing Vehicles
Announce Type: new Abstract: Flapping-wing aerial vehicles (FWAVs) demonstrate remarkable agility but face substantial autonomy challenges due to their high sensitivity to aerodynamic disturbances and limited sensor payload capacity. Current simulation platforms typically rely on oversimplified laminar flow assumptions and idealized sensor models, failing to capture the complex turbulence patterns and perceptual limitations encountered in real-world operation. This simulation-to-reality...
ClothTransformer: Unified Latent-Space Transformers for Scalable Cloth Simulation
arXiv:2605.27852v3 Announce Type: replace Abstract: Unified and scalable Transformers have recently achieved remarkable success in modeling diverse phenomena traditionally associated with computer graphics, such as 3D visual effects, rendering processes, and motion in videos. In this work, we take a step further by investigating whether modern Transformer techniques can tackle the challenging task of cloth simulation. To this end, we present ClothTransformer, a framework that reformulates...
ClothTransformer: Unified Latent-Space Transformers for Scalable Cloth Simulation
arXiv:2605.27852v2 Announce Type: replace Abstract: Unified and scalable Transformers have recently achieved remarkable success in modeling diverse phenomena traditionally associated with computer graphics, such as 3D visual effects, rendering processes, and motion in videos. In this work, we take a step further by investigating whether modern Transformer techniques can tackle the challenging task of cloth simulation. To this end, we present ClothTransformer, a framework that reformulates...
Long-term laser frequency stabilization with an FPGA-controlled scanning cavity
arXiv:2606.09720v1 Announce Type: new Abstract: We present an FPGA-based implementation of a scanning transfer cavity lock (STCL) for laser frequency stabilization, allowing for the simultaneous stabilization of multiple laser sources with respect to a single reference laser by means of a continuously scanned Fabry-Perot cavity. By exploiting the FPGA architecture to simultaneously perform cavity scanning, peak detection, and feedback actuation, we minimize latency and allow independent...