Applied & Human-Centered · Computer Science & AI
Robotics
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4,418 papers, from 4 September 2026 to 5 November 2026: 4,418 arXiv preprints.
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Newest papers, page 114
MobileVISTA: Generative Data Augmentation for Pose Generalization in Mobile Manipulation
Mobile manipulators such as humanoid robots are increasingly deployed in dynamic, unstructured environments to perform dexterous manipulation tasks.ProCut: Probabilistic Cutting Topology for Autonomous Electrosurgical Tissue Dissection
Accurately modeling and tracking the deformation of soft tissue is critical for a wide range of interventional and surgical procedures.ReDex: Repairing Sim-to-Real Dexterous Policies by Finger-Level Compliant Interaction
Dexterous manipulation policies trained in simulation often fail to transfer to the real world because of errors in contact timing and force regulation.Task-Space Imitation Guidance for Efficient Reinforcement Learning
We introduce Task-Space Imitation Guidance for Efficient Reinforcement Learning (TIGER), a reward-construction and pretraining framework for sparse-reward tabletop robotic manipulation.HexaGripper: A Single-Actuator, Winch-Deployed Gripper for Autonomous Aerial Parcel Collection
Autonomous aerial parcel collection remains constrained by package-transfer operations that require manual loading, landing, or dedicated ground infrastructure.CIRRA: Dual-Level Continual Instruction Reconciliation with Ongoing Execution for Embodied Robot Agents in Interactive Household Tasks
Household robots must accommodate new user instructions while executing ongoing tasks.Trajectory Planning without Trajectory Data: A Manifold-Guided Approach
A common way for trajectory planning is to leverage generative models trained on large collections of expert trajectories.Tackling Sim-to-Real Mismatch Through Sampling-Based Disturbance Observers: From Analytical Models to Learned World Models
Robotic controllers increasingly rely on analytical models, simulators, cost-query interfaces, and learned world models.GJK-CBF: Control Barrier Functions for Convex Rigid Body Collision Avoidance on SE(3)
Collision avoidance among convex bodies is a fundamental problem in robotics.$R^2$-WAM: Repair-and-Reject Post-Training for World Action Models
World Action Models (WAMs) emerge as a promising foundation for policy refinement by predicting the consequences of sampled actions.PreAct-Nav: Agentic Reasoning Before Action for Urban Navigation
Urban navigation requires embodied agents to pursue long-horizon goals through local decisions based on egocentric observations.Nudge Before You Push: Physics-Aware Navigation via Tactile Probing
Visually identical containers can conceal loads that require different handling decisions.RobotUse: Allocating Computation, Context, and Decisions
Robot agents must connect their intended actions to observed outcomes while retaining the context needed to revise their choices over repeated attempts.DiVeR: Decision-Critical Verifier Learning for VLA Test-Time Scaling
Scaling robot data and model capacity has improved Vision-Language-Action (VLA) policies, but further progress is constrained by the high cost of robotic data.Orchestrating Level-$K$ Policies Against Unknown Opponents in Partially-Observable Dynamic Games
Level-$K$ reasoning generates a hierarchy of policies specialized to opponents with different reasoning levels.A Unified Dynamics Framework for Reinforcement Learning and Classical Control of a Six-DOF Pipeline-Tracking ROV in NVIDIA Isaac Sim
Reinforcement learning controllers for underwater vehicles are usually trained against one physics representation and deployed against another, so reported performance does not always describe…FreeLoc: Online Floorplan Localization via Diffusion-Aided Pose Refinement
Floorplans provide compact and widely available geometric maps for indoor localization, but existing high-performing floorplan-based methods still convert them into dense scene-specific offline…LightVLN: Efficient Aerial Vision-and-Language Navigation with Compact Memory and History-Guided Local Aggregation
Aerial vision-and-language navigation (VLN) enables unmanned aerial vehicles to execute long-horizon natural-language instructions from visual observations in complex three-dimensional environments.GeoBridge-VLA: Geometry-Aware Residual Adaptation for Vision-Language-Action Models
Vision-language-action (VLA) models encode semantic information from vision-language pretraining, but manipulation also requires precise spatial reasoning.Beyond LLM Serving: Characterizing Vision-Language-Action Workloads for Embodied AI System Design
Vision-language-action (VLA) models translate multimodal observations into low-level robot actions.