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 71
What Matters for World Modeling in Vision-Language-Action Models?
Integrating world models into Vision-Language-Action models (VLAs) has emerged as a promising direction, enabling policies to anticipate future dynamics beyond reactive observation-to-action mapping.FOMI: A Force-Feedback Manipulation Interface for Teaching Contact-Rich Manipulation
Robot-free collection with handheld interfaces enables scalable acquisition of human demonstrations for policy learning.Active Perception of Upper-Limb Functional Mobility through Human-Robot Handovers
The reintegration of people in the workplace after an upper-limb injury is often a long process.MUCO: A Mani-Unit-Structured Manipulation Framework for Compositional Long-Horizon Robot Tasks
Learning and executing long-horizon robot manipulation as complete task trajectories raises data-collection costs, lim?its capability reuse, and causes local failures to cascade into later task…Complementary Future Token Pruning for World Action Models
World action models (WAMs) jointly predict future visual states and robot actions, but processing dense future-frame tokens incurs substantial inference latency.Why 3D Reconstruction Breaks Down on Under-Ice AUV Video, and How to Predict It
Reconstruction of 3D structures using under-ice AUV video footage has been inaccurate, although it is not certain whether this is due to shortcomings in the methods or an inherent deficiency of the…MorphAct: Robot Policies Morphing with the Worlds They Act In
Progress toward general intelligence in the physical world requires scaling robot learning across diverse environments and interactions.FoveaVLA: Foveation Actions Replace the Wrist Camera in VLAs
We present FoveaVLA, a Vision-Language-Action (VLA) model that replaces the wrist camera with learned foveation actions.HM3D-M3: A Benchmark for Multi-Agent, Multi-Modal, Multi-Object Goal Navigation
Rapid progress in AI agents and robotics makes it a matter of the near future that humans are served by a team of robots.Tactile-Guided Robot Learning: From Representation Learning to Foundation Models
Tactile sensing is becoming central to robust, adaptive, and dexterous robotic manipulation.Enabling Tidying Tasks in Robotic Vacuum Cleaners via a Geometry-Induced Self-Locking Deployable Linkage
Robotic vacuum cleaners must extend their functionality within tight limits on size, cost, and durability.Atomic-WAM: Execution-Grounded Atomic-Motion Reasoning for World Action Models
World Action Models (WAMs) typically adapt video foundation models to robotic control through joint video and action prediction.Investigating Behavior Cloning from Few Demonstrations for Autonomous Driving based on Bird's-Eye View in Simulated Cities
This paper investigates the use of Behavior Cloning (BC) for autonomous driving from a bird's-eye view (BEV) perspective in simulated urban environments.ObjDream: Guiding Vision-Language-Action Models with Object-Level Understanding and Future State Prediction
Vision-language-action (VLA) models have emerged as a powerful paradigm for robotic manipulation, enabling robots to generate actions from visual observations and language instructions.Smart Fusion for Adaptive Visual-IMU Weighting in cuVSLAM Sparse Bundle Adjustment
In cuVSLAM, visual and inertial measurement unit (IMU) residuals are fused in sparse bundle adjustment (SBA) with a weighting fixed by pre-calibrated noise covariances, leaving no mechanism to adapt…Learning Navigation from Multimodal Demonstrations with Geometric Candidate Modes
Offline navigation demonstrations are multimodal, because one observation often allows several valid actions, such as passing an obstacle on either side.FPTAS for Polygonal Multi-Robot Motion Planning
We study multi-robot motion planning in a polygonal environment with polygonal robots.Safe Reinforcement Learning with Receding-Horizon Safety Critic and Differentiable Action Shields
Despite the Markov assumption, safety failures in robot reinforcement learning rarely occur instantaneously; they typically emerge over several steps as the policy enters unfamiliar states under…Learning-Based Adaptive MPC for Magnetorquer-Only Satellite Attitude Control
Nanosatellites (e.g., CubeSats) have the potential to carry out useful science and exploration activities for outer solar system exploration, but their small size leads to tradeoffs between attitude…Efficient Test-Time Adaptation For Robot Policies
Reinforcement-learning policies for robot locomotion can fail at deployment when operating conditions shift (e.g., rough or slippery terrain, payload changes, sensing degradation), and retraining or…