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 180
BEACON: Belief-Enabled Adaptive CONtrol for Imitation Learning under Uncertainty
Robot manipulation tasks often involve hidden state information that cannot be directly observed and must be inferred through sequential physical interactions.Rapidly-Iterating Grid-Based Near-Optimal Kinodynamic Motion Planning
This paper develops the Rapidly-iterating kinoDynamic Grid (RDG) algorithm, an asymptotically near-optimal kinodynamic motion planning algorithm that produces high quality solutions through rapid…Distributed Infrastructure Sensors and Cues for Robotic Fire-Fighting and Safety System on a Lunar Base
There are renewed efforts to build a lunar base and house a team of astronauts on the Moon for extended periods.Task-Oriented Co-Design and Optimization of Geared Actuators for Robotic Applications
Different tasks performed by legged robots impose distinct torque and speed requirements on actuators.Expert-Play Contouring Control: Faster-than-Demonstration Planning from Slow Expert and Fast Play
Expert demonstrations often specify what a robot should do, but not how fast it can do it.ARCGym: Benchmarking Deep Reinforcement Learning in Autonomous Robotic Colonoscopy
Simulations for learning-based autonomous colonoscopic navigation focus mainly on fully actuated capsule robots, failing to capture the contact-rich navigation of long and flexible clinical…Kinematic Interface for the Wild: Modular Bimanual Loco-Manipulation Capture from 360$^{\circ}$ Cameras Alone
A wrist-mounted camera for UMI-style data collection must do two jobs: record the manipulation and localize in the scene.Commonsense-Grounded Path Planning from Abstract Instructions
We present \emph{commonsense ranked search} (CoRS), a novel path planner that turns an abstract instruction into a route that follows commonsense.Whole-Body UMI: Transferring UMI Manipulation Skills to Humanoid Whole-Body Manipulation via Real-Time Motion Generation
Collecting whole-body demonstrations for humanoid manipulation mostly relies on teleoperation, which is costly and hard to scale up.ForceRFT: Refining VLA Actions through Force-Guided Residual Reinforcement Learning
Force-conditioned vision-language-action (VLA) policies can respond to contact, but when trained solely on demonstrations, their recovery behavior may be limited by demonstration coverage, and they…Physical-Touch Observability from Wrist Wrench in Granular Scooping
Mining and earthmoving are important real-world deployment settings for embodied intelligence.SmoLSTM: A Compact Vision-Language-Action Model with Recurrent Memory that Persists
Vision-language-action models often predict actions from only the current observation, which can leave tasks involving object occlusion or visually identical objects ambiguous without episode history.Image Frame Dynamic Object Segmentation and Ego Motion Estimation using Radar Image Fusion
Dynamic object segmentation and ego-motion estimation are closely coupled problems in autonomous driving, as accurate ego-motion estimation typically requires static scene observations, while…PileBelief: Persistent Physical State for Interaction-Driven World Modeling
World models allow robots to anticipate action consequences before execution.A Reconfigurable Dual-Opposition Architecture for Single-Hand Assembly and Manipulation
In-hand assembly is constrained by the need to maintain grasps on two separate parts while controlling their relative motion within a single hand.Barrier Certificate Synthesis for Non-Polynomial Robotic Dynamics via Polynomial Lifting
Safe operation of robotic systems requires trajectories to remain within a prescribed safe set under admissible control inputs.Stable and Efficient Real-World Online VLA Post-Training via Asynchronous Replay-Anchored Policy Improvement
Online post-training of vision-language-action (VLA) models requires efficient use of robot interaction and reliable policy improvement from continually collected experience.H-VLA: Hierarchical Vision-Language-Action Model with Key-Action Reasoning and Motion Planning in a Unified Action Space
Vision-Language-Action (VLA) models have shown strong potential for robotic manipulation, but many existing methods still rely on direct mappings from language and visual observations to dense…Computationally efficient safe exploration in reinforcement learning
Reinforcement learning in real-life applications requires safety guarantees during exploration."Dear LLaVA, Please Drive": A Depth-Aware Vision-Language Agent for Closed-Loop Robotic Control
Vision-language models (VLMs) provide a compelling foundation for reasoning-driven mobile navigation, offering rich contextual understanding and strong generalization from large-scale pretraining.