Search: “hardware”

Cost-Accuracy Trade-offs: Neural Operator vs Classical Numerical Solver

model-releasesarxiv-cs-lg

arXiv:2609.24021v1 Announce Type: cross Abstract: Neural operators are data-driven models that learn mappings from inputs that parameterize partial differential equations, such as spatially varying co

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Dexterous Robot Manipulation from Human Demonstrations via Contact-Anchored Retargeting and Residual Policy Learning

DGX agent

arXiv:2609.24093v1 Announce Type: new Abstract: Learning dexterous manipulation from demonstrations is bottlenecked by data: the contact forces that determine whether a grasp succeeds are absent from

safetyarxiv-cs-ro

22 Sept 2026

Experimental Evaluation of a Low-Power Ultra-Wideband Receiver for Spectrum Sensing

arXiv:2609.22134v1 Announce Type: cross Abstract: Walsh-sequence-based receiver architectures offer an alternative approach for the reception and reconstruction of multiple simultaneous RF signals ove

Kinematic Interface for the Wild: Modular Bimanual Loco-Manipulation Capture from 360^{irc} Cameras Alone

arXiv:2609.22809v1 Announce Type: new Abstract: A wrist-mounted camera for UMI-style data collection must do two jobs: record the manipulation and localize in the scene. Most handheld devices localize

Learning tactile perception from high-bandwidth single-point sensing

arXiv:2609.24621v1 Announce Type: cross Abstract: Tactile sensing is increasingly being incorporated into learning-based robotic manipulation, yet many existing approaches rely on spatially distribute

safetyarxiv-cs-lg

ME-VLM:A Unified VLM for Embodied Cognition and Agent Coordination

arXiv:2609.24526v1 Announce Type: new Abstract: Physical AI requires models to ground visual and linguistic understanding in real-world environments while accounting for environmental constraints and

local-aiarxiv-cs-cv

MECAIL: Communication-Aware Incremental Learning for Object Detection with 14.6 KB Spatiotemporal Experts

model-releasesarxiv-cs-cv

arXiv:2609.24455v1 Announce Type: new Abstract: Intelligent transportation systems require Incremental Learning (IL) to continually improve their overall performance in dynamic environments. However,

Observing and Controlling Features in Vision-Language-Action Models

arXiv:2603.05487v2 Announce Type: replace Abstract: Vision-Language-Action models (VLAs) have shown remarkable progress towards embodied intelligence. While their architecture partially resembles that

OpenFlyScan: A Quality-Guided Aerial Reconstruction System for Consumer Drones

arXiv:2609.24253v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) provides high-fidelity scenes for large-scale embodied simulation, but constructing large-scale urban assets remains cons

Opt2VLA: Force-Aware Vision-Language-Action for Contact-Rich Humanoid Whole-Body Manipulation

arXiv:2609.23968v1 Announce Type: new Abstract: Humanoid robots are expected to perform diverse human-level tasks in daily environments, many of which require precise regulation of interaction forces.

Performance-Preserving Online Adaptation in Social Navigation via Diffusion Steering

arXiv:2609.24317v1 Announce Type: new Abstract: In social navigation, modeling the complex interactions between humans and robots is difficult, and deep reinforcement learning has therefore been activ

PINGU: Extending Air-Bearing Spacecraft Emulators with Open-Source Actuators and Learned Control for Contact-Rich Proximity Operations

model-releasesarxiv-cs-ro

arXiv:2609.23554v1 Announce Type: new Abstract: Low-cost planar air-bearing testbeds have matured into a standard proxy for free-flying spacecraft GNC, but they remain largely thruster-only and are ra

PredActor: Predictive Action Diffusion for Steerable Onboard Humanoid Control

arXiv:2609.24840v1 Announce Type: cross Abstract: Diffusion models offer flexible motion generation, but translating this flexibility into feedback-responsive humanoid control remains challenging. Hie

safetyarxiv-cs-lg

PRQuant: Permutation Residual Quantization for Low-Overhead Inference

arXiv:2609.22106v1 Announce Type: cross Abstract: Accuracy of Low-bit quantization of linear layers is often dominated by a small number of outliers. Although existing methods, such as smoothing, rota

Real-Time Plasma State Prediction via FPGA-Accelerated Quantized Recurrent Probabilistic Neural Networks

arXiv:2609.23141v1 Announce Type: cross Abstract: Real time plasma state estimation for control of Tokamak devices are challenging due to the stringent latency requirements of the plasma control syste

Agents

SCRAMPPI: Contingency-Constrained Planning using Hamilton-Jacobi Reachability

arXiv:2603.26995v2 Announce Type: replace Abstract: Autonomous robots commonly aim to achieve a nominal objective while minimizing a cost. Without contingency preparation, this can leave them vulnerab

agentsarxiv-cs-ro

Semi-automated reconstruction of indoor geometry from 360-degree video for CFD-based airflow analysis in classrooms

model-releasesarxiv-cs-cv

arXiv:2609.23425v1 Announce Type: new Abstract: Computational Fluid Dynamics (CFD) is widely used to evaluate ventilation and contaminant transport in occupied buildings, but deployment at scale is li

SPHQuant: Efficient extreme low bit weight quantization for Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.24875v1 Announce Type: new Abstract: Recent foundation models are moving toward native multimodal Vision-Language Models (VLMs), making VLMs a central form of next-generation foundation mod

Stability-Aligned Residual Adaptation for Rapid Recovery from Dynamics Shifts

arXiv:2603.07775v2 Announce Type: replace Abstract: Robotic systems deployed beyond controlled environments encounter abrupt and unobserved dynamics shifts that induce substantial transient performanc

local-aiarxiv-cs-ro

Steerable and Reactive Grasping Through Modular Design with a Three-Point Interface

arXiv:2609.24896v1 Announce Type: new Abstract: Dexterous grasping requires deciding where to grasp, reaching the target, and maintaining stable contact. We connect these stages through a compact thre

local-aiarxiv-cs-ro

STRIDER: Stepping-Enabled Multi-Gait Hierarchical 3D Loco-Manipulation Framework for Humanoid Robots

arXiv:2609.23483v1 Announce Type: new Abstract: Humanoid loco-manipulation faces two prominent limitations: controllers using continuous velocity commands cannot precisely regulate individual foothold

Think Like a World Model, Act Like a VLA: Distilling World-Model Representations into Compact Robot Policies

arXiv:2609.24682v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models map observations to actions with no objective that accounts for how the world responds, so their robustness is bou

safetyarxiv-cs-cv

Tutorials

Topology-Informed Visual Prompting For Vision Language Action Policies

arXiv:2609.23944v1 Announce Type: new Abstract: Vision-language-action (VLA) policies can struggle with manipulation tasks with complex obstacle geometries due to partial observability. These complex

tutorialsarxiv-cs-ro

Transformer-Based Warm-Starting for Feasible and Optimal Terminal Approach to Tumbling Objects with Space Manipulators

arXiv:2606.17317v2 Announce Type: replace Abstract: Autonomous capture of a tumbling object with a space manipulator requires trajectory generation under real-time onboard constraints. However, couple

Visuomotor Robotic Pruning in Planar Orchards Using Hybrid Reinforcement Learning

arXiv:2609.24906v1 Announce Type: new Abstract: Dormant tree pruning is labor-intensive yet essential for maintaining modern high-productivity fruit orchards. In this work, we focus on pruning of mode

Watching Quantum Models Think: Hilbert-Space Interpretability in Quantum Transformer Blocks

arXiv:2609.23016v1 Announce Type: cross Abstract: Deep learning models are powerful but opaque. As quantum machine learning matures, the field faces a defining choice: build quantum models that are eq

Applications

WiNeRF: Measurement Constrained Radiance Fields for Actionable Wireless Channel Modeling

arXiv:2609.22132v1 Announce Type: cross Abstract: Wireless embedded systems increasingly rely on wireless channel information for decision making, yet practical platforms operate under severe constrai

applicationsarxiv-cs-lg

Do small language models know what they don't know?

model-releasesarxiv-cs-cl

arXiv:2609.20824v1 Announce Type: new Abstract: We explore whether entropy-based confidence signals can be leveraged to improve the accuracy of Small Language Models (SLMs) with fewer than 3 billion p

Elastic Threshold Attention: Learned Contextual Sparsity for Long-Context Decoding

arXiv:2609.20888v1 Announce Type: new Abstract: Massive KV caches can cause severe memory-bandwidth bottlenecks during long-context decoding. Sparse attention methods mitigate this via selective loadi

local-aiarxiv-cs-lg

From Trainability Diagnostics to Optimization Claims: Boundaries and Controls in Variational Quantum Optimization

arXiv:2609.21243v1 Announce Type: cross Abstract: Barren plateau diagnostics characterize whether gradient signal remains available for training, but surviving signal need not translate into successfu

Learning Distance-Conditioned Object Transport for Humanoid Loco-Manipulation from a Single Motion Clip

arXiv:2609.21467v1 Announce Type: new Abstract: Motion tracking can reproduce humanoid loco-manipulation from a single retargeted motion clip, but a policy trained on a fixed reference primarily repro

Learning End-to-End Control for Omnidirectional Aerial Motion on Overactuated Tilt-rotor Quadrotors

arXiv:2602.21583v2 Announce Type: replace Abstract: While reinforcement learning (RL) has been successfully applied to conventional quadrotors for agile and robust flight, whether actuator-level RL ca

LIMBO: Learning and Internalizing Model-Free Barrier Objectives for Agile and Safe Whole-Body Control

arXiv:2609.22075v1 Announce Type: new Abstract: Safe whole-body control requires coordinating collision avoidance and balance under high-dimensional, nonlinear dynamics--making safety certificates dif

OpenSAL360: Open-Source Crowdsourcing Platform for Omnidirectional Video Saliency Collection

arXiv:2609.21480v1 Announce Type: new Abstract: Omnidirectional video saliency prediction plays an important role in many immersive multimedia applications, including viewport-adaptive streaming and c

Predictive Suppression Layers for Communication-Efficient Spiking Neural Networks

arXiv:2609.21583v1 Announce Type: cross Abstract: Feedforward Spiking Neural Networks (SNNs) typically propagate every generated spike indiscriminately, disregarding whether the information is redunda

Applications

Project SCOUT: Interceptor Drone for Perimeter Defense

arXiv:2609.21005v1 Announce Type: new Abstract: The rapid proliferation of unauthorized unmanned aerial vehicles (UAVs) has created a growing need for robust, jamming-resistant counter-UAV systems for

applicationsarxiv-cs-ro

RAYA: Learning Where and When to Intervene for Robot Recovery

arXiv:2609.21690v1 Announce Type: new Abstract: A robot can predict failure and still be unable to prevent it. By the time a safety mechanism reacts, the nominal plan may already have spent the contro

Tutorials

Sparse Identification for Automatic Large-Scale Screening: A Constraint-Aware Framework with Ultra Fast Decoding Algorithm

arXiv:2609.21321v1 Announce Type: cross Abstract: In the early stages of a pandemic, identification of a small number of infected individuals through large-scale screening is critical for pandemic con

tutorialsarxiv-cs-lg

Stability-aware Residual Reinforcement Learning Framework for Robotic Manipulator Disturbance Compensation

model-releasesarxiv-cs-ro

arXiv:2609.21307v1 Announce Type: new Abstract: Although conventional controllers and disturbance observers (DOBs) are the standard for precision tracking in manipulators, they suffer from parameter u

Stochastic Neural Signed Swept Volume for Real-time Chance-Constrained Trajectory Optimization

arXiv:2609.21211v1 Announce Type: new Abstract: Collision-free motion planning requires reliable collision models from sensed environments and validation of states along a continuous trajectory. To ma

Towards Effective Visual-Inertial SLAM with Passive-Only Sensors for Low-Cost Autonomous Underwater Vehicles

model-releasesarxiv-cs-ro

arXiv:2609.21015v1 Announce Type: new Abstract: Improvements to Visual-Inertial Simultaneous Localization and Mapping (VI-SLAM) for low-cost autonomous underwater vehicles (AUVs) are critical for tran

ZeroTouch: Tactile-Supervised Visual Contact Estimation for Contact-Rich Manipulation

arXiv:2609.21726v1 Announce Type: new Abstract: Reliable robotic grasping benefits from estimating the evolving physical interaction and selecting a grasp-dependent compression target. Tactile sensors

researcharxiv-cs-ro

A Noise Optimum in Rehearsal-Free Continual Learning: Isolation, Mechanism, and Scope

arXiv:2609.20162v1 Announce Type: new Abstract: Injecting stochastic noise into a consolidation rule can improve a network's retention of earlier tasks up to an optimal level, then degrade it -- an in

safetyarxiv-cs-lg

Accelerating Visual Policy Learning with Sampling-Based Model Predictive Control

arXiv:2609.20575v1 Announce Type: cross Abstract: Learning visual policies for locomotion and manipulation requires coordinating contact with the environment and can incur substantial computation and

local-aiarxiv-cs-ai

AI or Real: Detecting Partially Altered Videos Under Resource-Constrained Environments

arXiv:2609.20263v1 Announce Type: new Abstract: The proliferation of generative video models has shifted the practical detection threat from fully fabricated clips to partially manipulated footages. A

Before the Warning Comes Too Late: Incremental Phone-Scam Detection from Speech

model-releasesarxiv-cs-cl

arXiv:2609.20223v1 Announce Type: new Abstract: We study weakly supervised incremental telecom fraud detection from raw telephone audio, where training provides only conversation-level labels and pred

Compass-v3: Scaling Domain-Specific LLMs for Multilingual E-Commerce in Southeast Asia

model-releasesarxiv-cs-cl

arXiv:2509.09121v2 Announce Type: replace Abstract: Large language models (LLMs) excel in general-domain applications, yet their performance often degrades in specialized tasks requiring domain-specif

Compliance for Free: Learning Identifiable Impedance via Bilateral Teleoperation

arXiv:2609.19976v1 Announce Type: new Abstract: Vision-language-action models tell a robot where to move, but not how hard to push. Contact-rich tasks depend on that second quantity, compliance, yet n