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 208
Belief-Adaptive Online Autonomy for Quadrotor UAV Navigation under GNSS Degradation in Urban Environments
Reliable online autonomy is critical for quadrotor operation in urban airspaces, where global navigation satellite systems (GNSS) measurements suffer from multipath, blockage, and latency issues…World-Action Models for Robot Learning and Control: A Survey
Robots operating in open environments act under partial observability, physical constraints, and dynamic task contexts.AssemblyGrid v1: A Benchmark for Multi-Robot Production with Temporary Coalitions, Local Information, and Geometric Constraints
Flexible robotic production requires joint decisions on process progression, material routing, resource assignment, temporary cooperation, and simultaneous execution, since each decision can affect…How Well Do Pseudo-Rigid Body Models Capture Real Plants? In-Field Validation of Simulated Blueberry Canes
Many labor-intensive tasks in fruit production such as pruning require physically interacting with the plant (e.g., pushing, pulling, bending limbs, etc.).Compositional Shift Algebra: Extrapolating Mixed Robot Shifts Without Mixed Finetuning
Robot deployments rarely change one mechanism at a time: cameras, action interfaces, and physical dynamics often shift together.Does Online Gravity Estimation Matter? Revisiting a Silent Design Split in LiDAR-Inertial Odometry
LiDAR-inertial odometry (LIO) systems differ in whether they continue estimating gravity after initialization.How to Better Train VLAs: Lessons Learned From the REAL-I Challenge at ICRA 2026
How can robot policies learn more effectively from a fixed demonstration budget?GROOVE: Geometry-Guided Reduction of Operational-Space Jerk in VLA Execution
Chunked vision language action (VLA) policies execute several commands per query, but jerk within chunks and across replanning boundaries can induce oscillatory motion and sharp actuator transients.Decentralized Multi-Robot Task Allocation Under Degraded Communication: A Benchmark of Performance, Reliability, and Computation
Selecting a decentralized Multi-Robot Task Allocation (MRTA) method for embedded deployment on autonomous platforms requires considering more than route performance alone.Learning In-Hand Object Reaching to General 6D Poses
In-hand manipulation allows multi-fingered dexterous hands to reconfigure grasped objects without releasing and regrasping them.When Do Learned Priors Help Visual Inertial Estimation? A Controlled Study of Prior Integration, Calibration, Initialization, and Backend Consistency
Learned components are increasingly integrated into geometric visual--inertial estimators to provide motion, depth, bias, uncertainty, or confidence cues.Force-Aware Reinforcement Learning with Hybrid Sensorless Force Estimation for Wheeled-Legged Loco-Manipulation
Force-controlled loco-manipulation requires a whole-body policy to coordinate locomotion and arm motion while regulating end-effector interaction forces.GeomVLA: Unifying Scene, Motion, and Action in 3D
We present GeomVLA, a Vision-Language-Action (VLA) model that unifies perception, latent scene motion prediction, and action generation within a shared robot-centric 3D coordinate frame.LePlanner: An Iterative Amortized Controller For World Models
World models trained with joint-embedding predictive architectures learn compact, structured latent representations from physical interaction, yet planning in these latent spaces typically relies on…ReWeight: Leveraging Human Data for VLA Post-Training via Demonstration Retrieval and Sample Weighting
Post-training vision-language-action (VLA) models for specific robots and tasks requires in-domain demonstrations, yet collecting diverse robot data is costly.Co-Speech with You: Training-Free Personalization of Robot Co-Speech Gestures
Personal robots should adapt their co-speech gesture style to a new user without requiring model retraining.BLInD: Learning Driver Intent as a Distribution over Future Ego Trajectories
We present BLInD (Blind Learned Intent Distribution), a compact network that maps recent vehicle-state history (e.g. speed, curvature, indicator, and vehicle type) to a top-k distribution of future…Rethinking the Implications of Human Feedback for Preference Learning in Human-Robot Collaboration
In Human-Robot Interaction, the standard approach to learn a reward model that represents human preferences for robot behavior consists of three steps.What Makes an Efficient VLA? Navigating Action-Head Design, Scaling, and Latency
Vision-Language-Action (VLA) models combine a pretrained vision encoder, a language backbone, and an action head, but their relative contribution has not been established under controlled…Mobile Multi-Robot Navigation under Runtime Uncertainty via Koopman Operator Learning and Nonlinear Model Predictive Control
In this work, we developed a nonlinear model predictive control (NMPC) framework that employs learned dynamics via the Koopman Operator theory for mobile multi-robot navigation.