Applied & Human-Centered · Computer Science & AI
Robotics
The newest papers in Robotics that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
4,418 papers, from 4 September 2026 to 5 November 2026: 4,418 arXiv preprints.
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Newest papers, page 146
Agent Priors-guided Policy Learning
Robots that learn from a few demonstrations often require two forms of generalization.LQR-ArUco Fusion: Robust Hierarchical Control for Navigation and Asymmetric Manipulation in Two-Wheeled Robots
We propose a hierarchical control framework to address severe dynamic instabilities and navigational drift that arise when a two-wheeled inverted pendulum (TWIP) robot attempts asymmetric object…Humanoid Loco-Manipulation With Discrete VLA Model
Vision-language-action (VLA) models using discrete action tokens have proven effective for controling robotic arms on manipulation tasks.X-Reset: Scaling Object-Centric Reinforcement Learning via Cross-Embodiment Resets
Reinforcement learning (RL) in simulation can train dexterous manipulation policies without robot demonstrations, but training a single generalist policy with task-agnostic rewards faces a severe…RoboCompiler: Graph-Native Compilation of Closed-Chain Robots for Consistent Modeling, Control, and Simulation
Robots with kinematic loops, coupled actuators, and changing contacts require consistent models of configuration, motion, force, and dynamics.Statistical Learning of Contractive Dynamical Representations for Composite Adaptive Control
We present a representation-learning framework for composite adaptive tracking control under dynamically coupled disturbances.DexRoam: Learning Mobile Bimanual Dexterous Manipulation from Egocentric Whole-Body Human Demonstrations
Mobile bimanual dexterous manipulation requires continuous coordination of locomotion, whole-body motion, and finger-level dexterity within a single trajectory, creating a severe robot demonstration…Passive-Dynamic-Walking-Inspired Dynamics Guidance for Energy-Efficient Humanoid Locomotion
Learning energy-efficient humanoid locomotion requires discovering mechanically economical gait coordination, not merely reducing actuator effort.Systematic Multi-Agent Vision-and-Language Navigation: Formulation, Benchmark, and Method
Vision-and-Language Navigation (VLN) has largely focused on a single agent following a single instruction, yet many real-world applications require teams of robots to tackle tasks beyond the…In-Context Learning for Robots: Methods and Applications
General-purpose robots must infer what a new task requires and translate that understanding into appropriate physical action.CoDimRecon: Agentic Reconstruction of Sim-Ready 3D Scenes with Deformable Curves, Surfaces, and Volumes
Reconstructing simulation-ready 3D scenes from real-world observations enables robotics, gaming, and immersive applications, yet existing methods largely assume rigid objects.SAKI: Skill Assembly and Kinematic Imitation from Human Videos for Long-Horizon Mobile Manipulation
Learning from human videos offers a promising route to acquiring diverse manipulation skills.GeoWind2Plan: Mission-Time 3D Urban Wind Prediction for Energy-Efficient UAV Planning
In urban low-altitude flight, buildings reshape ambient wind into spatially varying 3D flow, making unmanned aerial vehicle (UAV) energy depend on local wind exposure as well as path length.AerialDojo-200K: A Large-Scale Benchmark Suite for Open-World Aerial Object-Goal Search
Open-world aerial object-goal search is a foundational yet challenging task, requiring aerial agents to autonomously explore large-scale, unstructured three-dimensional environments and reach target…MagNav: A Dual-Core Magnetic Track Guidance Framework for Lighting-Invariant Navigation in Two-Wheeled Robots
Two-Wheeled Inverted Pendulum (TWIP) robots are useful for studying how to control systems that are naturally unstable and have fewer actuators than degrees of freedom.Scouting the Dynamics Gap: Test-Time Policy Adaptation via Action-Outcome Feedback
While pretrained robotic policies exhibit impressive capabilities in controlled environments, unobserved physical properties and dynamics require these policies to rapidly adapt during deployment.KPI: A Promptable Kernel for Physical Interaction on Humanoids
Humanoids now walk, balance and reach with remarkable generality: one whole-body tracking policy follows references from a human, or from an end-to-end policy.SkillWeaver: Agentic Exploration over Neural Interaction Skills for Scalable Robot Data Generation
Large-scale demonstrations have driven unprecedented progress in robot learning, yet collecting robot data through teleoperation is expensive and difficult to scale to diverse environments and…Test-Time Adaptation of Manipulation Policies Under Actuator Degradation
Robot manipulation policies are usually trained under the assumption that a commanded action produces the same motion as it did during training even after hours of operation.ChronoSRL: Temporal Geometry for Self-Supervised Reinforcement Learning
A goal that is close in space can be far away in time.