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 131
Beyond Policy Alignment: Closing the Planning-Learning Loop for Robot Control with Learned World Models
Planning with learned world models combines online trajectory optimization with learned value and policy functions for high-dimensional control.ChunkTrust: Adapting Execution Horizons for Robot Policies with Action-Expert Evidence
Robot foundation policies predict action chunks, but how many actions to execute before replanning depends on the current task phase.Experience-Driven Continual Learning of Terrain Traversability for Quadruped Robots
Safe and efficient quadruped navigation over unfamiliar terrain requires predicting terrain-robot interaction before contact: geometry and visual appearance alone cannot reveal how the robot will…DiffWAM: A Fast and Efficient Navigation World Action Model
Pretrained video foundation models encode rich semantic and spatiotemporal priors for embodied navigation, yet converting these priors into UAV motion typically requires expensive future-video…Inline Memory Meets Reusable Skills: Memory-centric Framework for Vision-Language-Action Model
Vision-Language-Action (VLA) models have shown strong promise for general-purpose robotic manipulation, yet adapting them to new tasks and domains remains inefficient: existing methods often rely on…Tool-Policy Co-Design for Powder Weighing in Laboratory Automation
Autonomous powder weighing is one of many bottlenecks in laboratory automation due to the complex, non-linear dynamics of heterogeneous materials.Learning from Runtime Feedback through Failure-Bank Self-Evolution for Vision-Language-Action Models
Vision-language-action (VLA) models generalize broadly across robotic manipulation tasks, but complex environments require balancing task success with unintended contact.Toward Real-Time VLAs: Stage-Aware Two-Step Flow Denoising and System-Level Evaluation
Vision-language-action (VLA) models face a timing gap between low-rate inference and high-rate robot execution.RL-Guided PAC-NMPC for Probabilistically-Safe Perception-Based Navigation in Unknown Environments
In this paper, we present an approach for combining stochastic nonlinear model predictive control (SNMPC) and reinforcement learning (RL) to enable probabilistically-safe perception-based navigation…Magic-W0: A Structured World-Action Foundation Model for Physical Intelligence
World-action models (WAMs) augment robot policies with action-conditioned environment dynamics, yet existing approaches largely rely on future observation reconstruction or generic latent prediction…SplineWAM: Adaptive Action Horizons for World Action Models via B-Spline Representations
World action models (WAMs) are large embodied policies that jointly predict future video and the actions to execute, emitting a fixed-length action chunk per inference call.Markovian Dynamics Enforcer: Feasibility Preserving Correction on Learned Dynamics Manifolds
Neural trajectory predictors can reach low prediction error while violating dynamics, actuator limits, or state constraints, especially when controls are unobserved and dynamics are partially…Active Mapping of Underwater Litter Using Camera-Sonar Fusion
Marine litter is a growing threat to the underwater ecosystem, driving demand for autonomous survey methods that can locate debris efficiently over large areas.NavHarness: Adaptive Goals for Agentic Vision-Language Navigation
Vision-Language Navigation (VLN) requires embodied agents to generate actions based on instructions and observations.Magnetic based In-situ Self 3D Pose Estimation for a Modular Soft Tendon-Driven Continuum Robot via IMU-Fusion
Continuum robots are well suited for gentle manipulation because of their inherent compliance and ability to adapt to complex environments.TACTIC: Temporal and Context-Aware LLM Tactical Planning for Roadside LiDAR Attacks
Physical LiDAR attacks are often evaluated using fixed primitives and manually selected parameters, despite their strong dependence on surrounding traffic.PhasePlan: Ordered Future-Phase Planning for Robot Brain Models
Robot brain models integrate vision, language, and robot state to generate actions for complex manipulation tasks.When Instructions Retrieve Trajectories: Diagnosing and Mitigating Generalization Failures in VLA Models
Vision-language-action (VLA) models can exceed 90% success on in-distribution tasks and withstand nuisance changes that preserve the required action, yet fail under counterfactual changes that…EWAM: Emergent Depth-Wise Specialization in a Unified Embodied Model -- From Semantic Understanding through Visual Foresight to Action
Vision-language-action (VLA) policies emphasize semantic understanding, whereas world-action models (WAMs) learn predictive representations of environment dynamics.Multi-Link Safety Filtering for VLA Policies Around Moving Hazards
A vision-language-action (VLA) policy can finish a manipulation task while knocking over objects unrelated to it, so task success alone does not show that the policy is safe to deploy in clutter.