Applied & Human-Centered · Computer Science & AI
Robotics
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4,418 papers, from 4 September 2026 to 5 November 2026: 4,418 arXiv preprints.
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Newest papers, page 149
Safe Score Matching: Diffusion Policies with Hamilton-Jacobi Reachability for Online Safe Reinforcement Learning
Online safe reinforcement learning (RL) seeks policies that maximize reward while satisfying safety constraints.Traceable Human-to-Humanoid Sign Language Benchmarking
Sign data collection is costly, and teleoperation scales poorly, motivating reuse of large video corpora.Recursive Harness Distillation across Agents for Robot Manipulation
A central goal in robotics is to enable manipulation across changing tasks and environments.Large Language Models for Model-Based Robot Design
Large Language Models (LLMs) can contribute useful engineering knowledge to robot design, but directly generated designs may rely on implicit assumptions and provide no guarantees of feasibility or…TC-ADA: One-Shot Active Domain Adaptation for Semantic Segmentation
Manual dense annotation remains a major obstacle to deploying semantic segmentation models in new driving environments.VIDEAS: Distilling Explicit Action Semantics from Demonstration Videos for World Models via Prior-Guided Simulation
World models learn internal representations of environment dynamics to predict future states, enabling agents to optimize action plans without physical interactions.AMBIT: Anticipatory Multimodal Body Recruitment for Bimanual Tracking on a Humanoid
A humanoid with 5-DoF arms cannot track generic bimanual end-effector trajectories with its arms alone; pelvis and waist motion must be recruited, but which motion, and when, is not uniquely…AI-Driven Collaborative Assembly Line Inspection: System Integration and Deployment Challenges
Manual visual inspection on assembly lines is a persistent manufacturing bottleneck: operator fatigue over extended shifts lowers defect-detection rates.A Disk-Shaped Magnetoelastic Torque Sensor for Robotic Joints Using Permanent Magnetization
Direct torque sensing is a growing need in the robotics community to enable precise control and interactions where torque estimation from motor current is not sufficient.Steer2Grasp: Inference-Time Embodiment-Aware Steering for Diverse Physically Feasible Grasp Diffusion
Current grasp diffusion models provide rich priors for generation, yet their object-centric approach can violate the kinematic and collision constraints imposed by the embodiment and the environment.FoLD: Force-Informed Learning for Dexterous Articulated Object Manipulation
Transferring human demonstrations to dexterous robots remains challenging because differences in hand morphology and contact dynamics often cause retargeted motions to fail at producing the intended…SLIP-VLA: Single-Step Latent Imagination for Policy Learning in Vision-Language-Action Models
Vision-Language-Action models are increasingly effective for robotic manipulation, yet most predict actions directly from current observations without explicitly modeling future scene evolution.Beyond One-Step Accuracy: State-Affine Latent Transition for Reliable Visual Planning
Joint-embedding world models enable visual planning by learning action-conditioned dynamics in latent space.Hierarchical Multi-agent Reinforcement Learning for Warehouse Robot Coordination under Communication Loss
In this paper, we propose a hierarchical multi-agent reinforcement learning framework for coordinating robot teams in warehouse environments under communication loss.InfraVLA: Extending Vision-Language-Action Navigation with Infrastructure Cameras
Many indoor environments in which robots operate, such as warehouses, offices, and hospitals, already have cameras installed.Demonstration-Free Success-Probability Reward Learning for Generalist Robot Policies
Reinforcement learning (RL) enables generalist robot policies to improve through trial-and-error interaction, yet its effectiveness is fundamentally constrained by sparse task rewards.Observability-Informed Optimal Sensor Placement for Soft Robots
This paper presents the application and experimental evaluation of a systematic method for optimal sensor placement in soft robots.Does Adversarial Training Improve Generalization in Multi-View VLAs? Revealing and Mitigating View Collapse
Vision-language-action (VLA) models adapt pretrained vision-language models (VLMs) for closed-loop robot control, transferring their perceptual and semantic capabilities to action prediction.MomWorld: Momentum-Aware Latent World Model for Long-Horizon Autonomous Driving
Long-horizon planning enables autonomous vehicles to anticipate scene evolution and potential risks, supporting safe and stable decisions in complex interactions.AnyStep-WAM: Budget-Aligned Distillation and Adaptive Inference for World Action Models
World-action models (WAMs) couple predictive visual modeling with action generation, typically relying on iterative denoising with a fixed denoising steps.