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 32
GOFish: Full Field-of-View Gaussian Splatting and Mesh Extraction
Robots, autonomous vehicles, and consumer 360° cameras use fisheye lenses for wide fields of view (FoVs).Echo: Scaling Visual Reinforcement Learning with Off-policy Experience
Scaling visual reinforcement learning (RL) with GPU-accelerated simulation is computationally expensive due to rendering and visual-policy inference costs.When More Planning Hurts: Learned Planners for World Models
On PushT, our fixed action updater (1,505 parameters) solves 8 of 16 scenes reserved from our configuration selection.What Actually Matters? A Paired Evaluation of Inference Settings for $π_{0.5}$ on BEHAVIOR-1K
Vision-Language-Action (VLA) models offer a promising paradigm for general-purpose household robotics.3D Occupancy-Language Fields from mmWave Radar
Radar systems can recover scene geometry and recognize predefined categories, but these outputs do not provide a persistent spatial representation for open-ended language queries.FORGE: Feasible Online Reduced-Order Reference Generation and Whole-Body Execution for Agile Humanoid Locomotion
This paper presents a two-stage learning framework for versatile and agile humanoid locomotion that couples online reduced-order model (ROM) reference generation with whole-body tracking control.Active Constraints for Simultaneous Guidance and Safety in Handheld Micromanipulation
In micromanipulation, erroneous hand motion limits unaided manipulation accuracy, which can affect task performance and safety in critical applications like microsurgery.Self-Labeled Preference Transfer for Steerable Robot Manipulation
Vision-language-action (VLA) policies can learn to follow execution preferences, such as where to grasp an object or how to move around an obstacle, from demonstrations annotated with preference…METATRON: A Promptable Whole-Body Execution Layer for Humanoids
Humanoid controllers often require task-specific training despite sharing the need for balance and whole-body coordination.Learning from Relative Action Credit for Escaping Local Minima
Reinforcement learning holds the promise of robots that learn manipulation skills from interaction alone, without pretrained priors or demonstration data.EARS-Info: Information-Aware Event-Driven Reallocation for Multi-Robot Exploration
We introduce EARS-Info, an information-aware extension of Event-Driven Ant Reallocation Search for multi-robot exploration on OpenStreetMap-derived grids.Forward-Backward Map Matching for Airborne Magnetic Anomaly Navigation
Airborne magnetic anomaly navigation provides a passive, unjammable alternative to Global Navigation Satellite Systems positioning by matching magnetometer measurements against a lithospheric…Efficacy of Monocular Depth Estimation in Lunar Environments
Recent advances in monocular depth estimation have demonstrated highly accurate 3D reconstructions within in-distribution terrestrial domains.RobotAgentBench: Towards Open-world Robot Autonomy
Recent advances in vision-language-action (VLA) and world-action models (WAMs) have significantly improved robotic manipulation, yet deploying robots in the open world demands a higher level of…Dream to Assist: Intent-Conditioned World Models for Shared Vehicle Control
Assistive agents in shared-control settings face a dual challenge: acting proactively to align with the human's intentions while remaining legible enough for the human to comprehend and fluently…Video World Models Need Predictable Latents
Video world models trained on large-scale robot data promise a safe and scalable approach for learning and evaluating policies that act in the physical world.Benchmarking Obstacle-Conditioned Safety in Household Robot Navigation
Safe household navigation requires robots to regulate clearance and speed according to what an obstacle is and how close it is, without unnecessary conservatism.Resource-Performance Trade-offs in Intra-Aisle Robotic Picking: A Discrete-Event Simulation Comparison of Shuttle Configurations With and Without an Onboard Tote Lift
This study compares two implemented intra-aisle robotic-picking configurations through discrete-event simulation.VLA-HWBench: Where the Time Goes When VLA Models Run on Edge Hardware
Vision-language-action (VLA) models increasingly run on edge devices aboard robots, where inference latency constrains closed-loop robot control.Networked Humanoid Intelligence: Communication, Coordination, Collaboration, and Social Interaction
Humanoid robots are moving from laboratory platforms toward connected fleets that share workspaces, infrastructure, tasks, and knowledge with other robots and humans.