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 199
Winning a Won Game: Strict Reach-Avoid-Stay Control Barrier Functions for High-Dimensional Black-Box Systems
Robots must complete their tasks and maintain the achieved outcomes while avoiding safety failures at all times.GLAMDRING: Gait Learning And Morphology co-Design via Reinforcement LearnING of CPGs
Robots are moving out of the structured factory floor and into unstructured environments such as disaster sites, planetary surfaces, and agricultural fields, for which the right robot often does not…Pose-aware Legged Robot Semantic Exploration with Omnidirectional Perception in Confined Unknown Environments
Semantic exploration in confined environments requires both environment mapping and detailed observation of target objects.ParticleSplat: Self-supervised Object-centric Latent Particle Splatting
We present ParticleSplat, a self-supervised object-centric learning method that decomposes scenes into a set of latent ''particles'' representing semantic entities through feedforward 3D Gaussian…FASA: Feedback-Aware Sampling Adaptation for Efficient Diffusion-Based VLA Models
Diffusion-based Vision-Language-Action (VLA) models achieve strong performance in embodied tasks, but their iterative sampling imposes heavy computational and memory-access cost, blocking real-time…Self-excited actuation enables adaptive and resilient flapping-wing flight
The muscles that power insect flight fall into one of two categories: 1) synchronous muscles that contract under direct control from the nervous system, and 2) asynchronous muscles which have an…PIVOT: Perception-aware Independent Viewpoint Online Optimization
A fundamental assumption in robotic perception is that the sensor's field of view (FoV) is fixed relative to the robot body.AffordanceWAM: Affordance-Aware Joint World-Action Modeling for Robot Manipulation
Generalizable robot manipulation requires predicting how a scene will evolve, identifying where interactions are feasible, and determining how to act.Learning and Control Beyond Linearity: Towards a Non-asymptotic Theory for Bilinear Systems
This tutorial provides a unified view of the emerging area of bilinear learning and control.Dense to MoE Adaptation for Compact Vision Language Action Policies
Vision language action (VLA) policies continue to grow in parameter count, making deployment on resource-constrained robot platforms difficult.UniDex-ViTac: Learning Unified Visuo-Tactile Dexterous Manipulation Policy from Human Video Data
Human videos provide demonstrations of dexterous manipulation but lack robot-executable actions and tactile measurements.Beyond Gestures: Estimating Full Hand Pose and Contact Forces from Wrist-Worn Pressure Sensor Array
Capturing hand motion and interaction forces is critical for interactive computing, VR, and high-fidelity tactile demonstrations for robot learning.ProxiDex: Learning Dynamics-Guided Proximity Policy for Dexterous Manipulation
Multi-finger dexterous manipulation relies on stable hand-object interactions, yet these interactions are partially observable in practice.Learning to Optimize UAV Path Planning for Data Sensing in Wireless Sensor Networks
UAVs have emerged as highly flexible platforms for data sensing in Wireless Sensor Networks (WSNs).SAVLA: Symmetry-Aware Vision-Language-Action Models for Robotic Manipulation
Vision-language-action (VLA) models have become the dominant paradigm for language-conditioned robot manipulation.WholeBodyWAM: Generalizing Pre-trained World-Action Priors to Humanoid Loco-Manipulation via WBC-Grounded Coordination
World Action Models (WAMs) offer a promising approach to general-purpose robot manipulation by jointly modeling visual dynamics and actions.Weave: Learning Whole-Body Dexterous Loco-Manipulation from Human-Object Interactions
Learning humanoid-object interaction requires coordinating whole-body balance, locomotion, and dexterous hand contact to control both robot and object motion.Differentiable Mesh State Estimation via Factor Graph Inference for Deformable Object Reconstruction
Estimating deformable object states remains a fundamental challenge in robotics and simulation.IL-ACT: Imitation Learning with Adaptive Cartesian Tracking Control for a 30-ton Excavator
Autonomous excavator control is challenged by coupled kinematics, actuation lag, and uncertainty.World Models for Embodied Intelligence: From Plausible to Controllable to Actionable
World models connect perception and decision-making in embodied intelligence by maintaining hidden state, anticipating consequences, comparing interventions, and adapting when execution departs from…