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 37
HuGe: Scaling Humanoid Generalist Vision-Language-Action Models with Egocentric Experience
Extending Vision-Language-Action models (VLAs) to humanoid robots requires coordinated whole-body control and diverse demonstrations that are costly to collect in real-world scenarios.Robust Single-Parameter Point Cloud Registration using Truncated Lp Functions
We propose a novel method for robust point cloud registration with only one tunable parameter.AdaPolicy: Action-Driven Anticipatory Robot Policies via Next-Chunk Prediction
Endowing robot policies with anticipatory capabilities has proven effective in improving control performance.ScheNav: Schematic-Guided Object Goal Navigation
Object goal navigation requires an embodied agent to locate and reach target objects in complex environments.RynnVLA-Latent: Scaling Robotic Manipulation Foundation Models with 3D-Grounded Latent Actions
Scaling vision-language-action (VLA) models is constrained by scarce action-labeled demonstrations and incompatible control spaces across robot embodiments.EAST: Embodied AI Safety Testing via Systematic Fault Injection in Digital Twins
Task success is not a sufficient measure of safety for embodied artificial intelligence (AI), because robots may complete objectives while violating safety requirements.ThinkLocoManip: A Whole-Body Control Agentic Harness for Legged Loco-Manipulation
In this paper, we propose ThinkLocoManip, an agentic harness for legged loco-manipulation designed to tackle complex, long-horizon tasks in large-scale environments.On Distributed Sensing and Adversarial Localization of Narrowband Acoustic Sources for Offshore Data Center Monitoring
This report investigates an acoustic surveillance framework for localizing and tracking narrowband adversarial acoustic sources that threaten offshore data centers.AuRA: From Atoms to Bits through Autonomous Robot Interaction
Simulation enables robot-learning experiments at scale, but acquiring physics-informed digital twins often requires human manipulation and manual annotation of recorded interactions.Scaling Dexterous Manipulation via Action Representation Pretraining
Large-scale vision, language, and video pretraining has substantially improved the perception and generalization capabilities of robotic manipulation models, but action generation for complex…Nonlinear Control of Aerial Manipulator
This paper presents two controllers for a quadrotor equipped with a two-DOF robot manipulator that physically interacts with the environment.Trajectory Generation and Control for Quadrotors
In this project, I explored controller design and trajectory generation for a quadrotor.IntNet: A Communication-Driven Multi-Agent Reinforcement Learning Framework for Cooperative Autonomous Driving
Achieving safety in autonomous driving through Multi-Agent Reinforcement Learning (MARL) is a critical yet challenging task due to non-stationarity, partial observability, and the need for effective…TRIAGE: Efficient Vision-Language-Action Inference Needs Both Reuse and Pruning
Vision-language-action (VLA) models are increasingly used for robot manipulation because they map camera images and a language instruction directly to actions.How High Can GPT-6 Astra Climb in Contact-Rich Manipulation? PhysLadder: A Hierarchical, Matched Sim-Real Benchmark for Physical Interaction
We introduce PhysLadder, a hierarchical Sim-Real benchmark for evaluating physical interaction capabilities in contact-rich manipulation.Multimodal Socially Aware Framework for Human-Robot Interaction in Virtual Reality
Social robots must coordinate speech and movement while interpreting multimodal human input.Dual Gradient Consensus for Adaptive Learning to Transient Out-of-Distribution Disturbances in Quadrotor Control
Quadrotor trajectory tracking under unmodeled disturbances often relies on online residual adaptation, but short out-domain residuals can corrupt the learned disturbance model when constant-step…The German Tank Problem & Navigating by Scent
A robot searching for the source of an odor must eventually answer a notably hard question: have I arrived?What Does World Modeling Actually Improve in Robot Action Learning?
World Action Models (WAMs) combine future-video prediction with robot action learning, yet improvements in task success alone do not reveal how predictive supervision manifests in execution behavior…Intrinsic Goals for Autonomous Agents: Hierarchical Exploration Captures Future Volitional Action in Drosophila
Animals have a remarkable capacity for autonomy---driven by intrinsic motivation---without external sensory cues or extrinsic objectives, yet the computational mechanisms behind this ability largely…