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 121
HexVIO: Towards All-Day Stereo-Inertial Tracking Through Commodity DSPs
The ability of a device to localize itself within its surroundings is a fundamental prerequisite for spatial computing.Equivariant Visual-Tactile Diffusion Policy for Contact-Rich Manipulation
Imitation learning for contact-rich manipulation requires high-quality expert data that is expensive to obtain.KungfuAthleteBot: learning high-dynamic humanoid motion from video with unified robust recovery
Video is an abundant, inexpensive source of human motion data that is rich in extreme athletic behaviors.Native Action-Prior Learning from Videos for World Action Models
World action models integrate future visual dynamics with robot action prediction, but their scalability remains limited by the need for action-annotated robot trajectories.Bidirectional Voronoi-biased Exploration Curriculum for Reinforcement Learning
Long-horizon tasks with sparse rewards pose an exploration bottleneck for goal-conditioned reinforcement learning: a policy started from the initial state rarely reaches the goal and receives no…I2CD: Direct Image-to-Convex Decomposition for Simulation-Ready Collision Geometry
Physics simulators and motion planners require convex collision geometry, yet image-to-3D generative models output dense, frequently non-manifold visual meshes.MobiAgent: Dual-Loop Recursive Policy Self-Improvement for Long-Horizon Mobile Manipulation
Long-horizon mobile manipulation presents significant challenges due to compounding execution errors and capacity interference between locomotion and arm control.Detect and Suppress: A Mechanistic Defense against Adversarial Patches in VLA Models
Adversarial patches can disrupt Vision-Language-Action (VLA) models by manipulating visual observations, leading to failures in robot control.XGenAct: Geometry-Enhanced World Action Models through Cross-Task Generation
World action models (WAMs) have advanced robot control by predicting how observations and actions evolve over time.DR-IPC: Disturbance-Resilient Integrated Planning and Control for LiDAR-Based Quadrotor Navigation
LiDAR-based quadrotor navigation in cluttered environments remains challenging under external disturbances, particularly when obstacle-aware motion generation and disturbance-rejection control are…Autonomous Robotic Navigation for Endovascular Brain-Computer Interface Access
Endovascular brain-computer interfaces (BCIs) avoid craniotomy but require precise device delivery through anatomically variable cerebral veins.RATE: Risk-Aware Tactile Encoding for Contact-rich Robotic Manipulation
Tactile sensing is particularly valuable for contact-rich robotic manipulation.A Unified Framework for Empowerment and Predictive Control
Sampling-based model predictive control (MPC) is a powerful approach to trajectory optimization, but its performance depends on an informative cost function that often requires substantial domain…AVL-JEPA: Preventing Causal Dynamics Information Collapse In Joint Embedding Predictive Architecture World Models
Joint embedding predictive architectures (JEPAs) predict future latent representations without reconstructing observations, enabling world models to focus on high-level semantic dynamics.World Action Learning via Interaction-Centric Spectral Latent Guidance
Learning general-purpose robot policies requires large-scale real-world interaction data, yet collecting robot demonstrations remains expensive and difficult to scale.Bridging Frontier Reasoning and Robot Execution: From Autonomous Demonstration Generation to Dense Language Supervision
Recent advances in frontier models enable robot manipulation from only a few demonstrations, but high inference latency limits their use for real-time robot control.LLA-MPC on Embedded Hardware: Rapid Adaptive Control with Thousands of Parallel Models
We present a generalized implementation of Look-Back and Look-Ahead Adaptive Model Predictive Control (LLA-MPC), a learning-free framework for real-time, rapid adaptive system identification and…UniIntervene++: An Adaptive Intervention Agent for Efficient Real-World Reinforcement Learning
Online reinforcement learning (RL) enables robot policies to improve through physical interaction, but the assistance they require changes as their competence evolves.CORNAV: Construction-Aware Reasoning for Robot Navigation on Active Worksites
The construction industry faces persistent labor shortages, low productivity that costs the global economy over $1.6 trillion annually, and one of the highest injury rates among major industries.EyeRobot 2.0: Active Gaze for Precise Manipulation without Wrist Cameras
Inspired by human vision, we introduce a framework using active gaze to enable fine-grained bimanual manipulation with only a single stereo camera.