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 126
HumanoidToolBench: Benchmarking Humanoid Tool Use from Selection to Mobile Execution
As robotic hardware and learning methods advance, humanoids need tools to perform tasks beyond their inherent physical limits.GlassGuard: Verified Glass Plane Mapping for Robot Navigation
Transparent and specular surfaces pose a serious challenge to LiDAR-based SLAM and navigation because laser returns may pass through glass, leaving collision boundaries absent from the map.SkeleWAM: Skeleton World-Action Modeling for Efficient Robotic Manipulation
World action models (WAMs) combine robot action generation with future state prediction.DuoMind: Enabling Distributed Multi-Robot Coordination with Semantic Communication
Vision-language models (VLMs) and vision-language-action models (VLAs) have recently driven rapid progress in general-purpose robots, yet most progress has focused on single-robot settings.Watch, Infer, Coordinate: Inferring Robot Partner Constraints for Zero-Shot Coordination
Robots operating in the physical world will increasingly need to coordinate with other robots, particularly in manipulation tasks where an object may be too large or heavy for a single robot to…InterEvolve: Test-Time Evolution of Reward Programs for Humanoid Loco-Manipulation
We study test-time evolution for humanoid loco-manipulation: solving tasks that a controller was never trained for by repurposing its existing skills, improving from its own attempts, and retaining…FERPO: Forward Entropy-Regularized Policy Optimization
Several state-of-the-art methods for online reinforcement learning in continuous control improve policies using action gradients of a learned critic.Reconstruct, Practice, Go Real: Guided Self-Improvement for Embodied Agents
Building reliable robot capabilities across diverse tasks requires substantial human effort to develop and maintain skills, design rewards, and integrate perception with control.Awomo-SimDataEngine: Agentic Simulation-ReadyWorld Generation
Generating useful robot-training data requires more than visually plausiblescenes: objects must support interaction, placements must remain physicallyvalid, and tasks must admit repeatable execution.World-Calibrated Proposal-to-Action Flow for Vision-Language-Action Models
Flow-based Vision-Language-Action (VLA) policies generate action chunks by transporting samples from a task-agnostic isotropic Gaussian source.SoTa: Soft Tactile Skins for Dexterous Manipulation
A growing body of work suggests that tactile sensing gives robot policies contact information that complements vision in dexterous manipulation.NEEDLEWORK: Offline Rewriting of Robot Data with Verified Local Stitches
Robot demonstrations may contain useful behavior even when individual episodes are inefficient or unsuccessful.Filter-Aware Fine-Tuning for Safe Humanoid Whole-Body Tracking
Safe whole-body motion is essential for deploying humanoid robots in unstructured environments.SocialVLA: A Social Perception Gateway for Human-Reaction-Based Failure Detection and Recovery in VLA Manipulation
Vision-language-action (VLA) policies enable diverse robotic manipulation but can fail during execution without recognizing their own errors.Co-design Gym: A Unified Benchmark for Embodiment-Policy Co-optimization
Finding an optimal behaviour policy within a given environment is a widely studied problem in domains as diverse as games, robotics, energy infrastructure, communication networks, and multi-agent…Rethinking World-Action Model for Compositional and In-Context Robotic Manipulation
Long-horizon compositional manipulation has become increasingly important for real-world robot deployment, where a single task involves multiple coordinated subtasks.Network-in-the-Loop at Scale: GPU-Batched 5G Simulation for Massively Parallel Robot Learning
Massively parallel GPU simulators train multi-robot policies in thousands of environments, and many fleets use private Fifth-Generation (5G) networks, where each robot's delay depends on its…Keep the Effect, Drop the Actor: Programmable Effect-to-Execution World-Action Models
A robot demonstration records two things in the same frames: what happened to the objects, and how one particular arm made it happen.Autonomous mobile robot operations logistics: a dataset of jobs, dispatch events and robot states
Autonomous mobile robots (AMRs) increasingly perform material transport in production logistics, where their operation is governed by job generation, dispatching and robot control.OpenRUA: Robot-Use Agents Are Zero-Shot Visuomotor Policies
Coding agents are extending their reach into the physical world by writing and executing robot control programs.