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 194
Not All Layers Need Tuning: Diagnosing and Directing Adaptation in Vision-Language-Action Models
Fine-tuning a Vision-Language-Action (VLA) model for a new deployment environment is expensive, yet most methods apply uniform-capacity adapters to every network region as if every region requires…ReRadar: Robust Radar Global Localization via Rotation-Equivariant Descriptor Learning
Global localization with scanning millimeter-wave radar remains challenging because place-recognition descriptors often discard spatial structure needed for accurate pose retrieval.Beyond Pixel Similarity: Task-Aware Evaluation of GAN-Based Synthetic Sonar Data for Robotic Perception
Synthetic data can reduce the cost of collecting and annotating training data for robotic perception, but generating sensor observations that preserve the characteristics relevant to downstream…Technical Report: One-Step Drifting Action Heads for GR00T N1.7
One-step action generation can substantially reduce the inference cost of vision-language-action (VLA) policies, but its effect on closed-loop task success remains an open question.A Comprehensive Review of Generative Physical Artificial Intelligence
The integration of large-scale foundation models with physical embodiments has led to significant advancements in robotics known as Generative Physical Artificial Intelligence (GPAI).OpenDexGrasp: Open-vocabulary Task-Oriented Dexterous Grasping
Dexterous grasp synthesis has advanced rapidly in generating stable and physically plausible hand poses, but real-world manipulation requires grasps that preserve the function implied by the task.Fetch My Beer: Synthetic-to-real Hierarchical Policy for Smooth Pick-and-place
Many real-world robotic applications require dynamically sensitive manipulation, where success depends not only on reaching a target state but on maintaining stable object dynamics throughout…"Your Robot Was Trained on a Lie": Collision Mesh Poisoning Attacks on Robotic Manipulation
Learning-enabled robotic manipulation increasingly relies on robot simulators for policy training and evaluation before real-world deployment.PRISM: Predictive Representation of Interaction Style and Motion for Social Robot Navigation
Humans often observe others before interacting and adjust their behavior accordingly.Prior Evolution and Task Alignment for Aerial Grasping
Aerial grasping is a remarkable capability exhibited by predatory birds, allowing them to capture prey through highly coordinated maneuvers in flight.Energy-Regularized Imitation Learning for Force- and Work-Aware Robotic Manipulation
This paper studies energy-aware manipulation as a physically grounded learning problem.LUMO: Designing Luminous Contact Morphology for Repeatable Whole-Finger Contact Observation
A low-impedance robot finger reports through joint torque how strongly it is loaded, but the same torque can arise from a small force near the fingertip or a large force near the joint.Characterizing Replay Retention Under Dynamics Shift in Model-Based Reinforcement Learning
Adapting to changes in robot dynamics requires learning from new data without discarding experience that may still be useful.Approximating High Dimensional Self-Motion Manifolds via Deep Generative Models
Self-motion manifold (SMM) characterizes the geometric structure of the infinite inverse kinematic solutions set of a redundant manipulator at a fixed end-effector pose, and its efficient recovery…TacBPM: A Tactile-conditioned Behavior Prior Model for Dexterous Reorientation
Dexterous in-hand manipulation requires policies that coordinate high-DoF hand joints through intermittent, contact-rich interaction.OmniRisk: Omnidirectional Trajectory-Risk Learning for Agile Quadrotor Dynamic Avoidance
Agile quadrotor avoidance of fast-moving obstacles requires anticipating collisions and selecting feasible maneuvers within short reaction windows.WAVE-Go: World-Model Navigation with Adaptive Execution for Wheel-Legged Robots
World models can anticipate the consequences of navigation actions, but predicted action sequences may become invalid during execution, especially when wheel-legged robots encounter dynamic…WholeBodyWAM: Learning Whole-Body World Action Models with Scalable Motion Priors
Humanoid whole-body manipulation requires coordinated whole-body dynamics, yet large-scale trajectories from a target robot are expensive to collect and difficult to scale.Reinforcement Learning for Real-Time Vision-Language-Action Policies
Reinforcement learning fine-tuning on top of large, pretrained Vision-Language-Action (VLA) models offers promise for highly reliable robot deployment.CANTABILE: Learning Expressive Dynamics for Robotic Piano Performance
Robotic piano playing has emerged as a standard benchmark for dexterous bimanual manipulation, yet progress on it has been measured almost entirely by note accuracy -- which keys are pressed (pitch)…