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 52
SPAR: Search-trained Push Action Ranker for Efficient Navigation Among Movable Obstacles
Navigation Among Movable Obstacles (NAMO) requires a robot to rearrange objects that block access to its goal.CAPSafe: A Benchmark for Contextual Action and Plan Safety Reasoning in Embodied Agents
Reasoning about safety is essential for embodied agents powered by large language models (LLMs).Plausible Future, Wrong Choice: Steering World-Action Models toward Intended Future
World-Action Models (WAMs) have emerged as a promising paradigm for embodied generalist policies by jointly modeling future world evolution and robot actions across diverse manipulation tasks.Physical AI for Intralogistics: Benchmarking the NVIDIA Sim-to-Real Ecosystem for Cosmos-Enhanced COMPASS Navigation on Industrial Mobile Robots
Classical robot navigation stacks are reliable but often require re-engineering for each new robot type and site.GPT-6-Astra Understands Touch and Outperform Vision--Tactile--Language--Action Models
General-purpose multimodal models have shown promise as direct robot action policies, yet whether they grasp the physics underlying real-world interactions and can apply that understanding to guide…MARE: An Open-Source Lunar Rover Simulator with Shadow Ground Truth for Perception and Autonomy
Lunar surface exploration increasingly relies on autonomous rovers that must perceive and traverse unstructured terrain under extreme illumination conditions.Fast Motion Retargeting Pipeline for Scalable Humanoid Robot Learning
While large-scale human motion capture datasets provide a rich source of demonstrations for humanoid robot learning, retargeting the diverse motions to different humanoid robots remains a nontrivial…CLOSER: Evidence-Aware Active Visual Verification for Embodied Object-Goal Navigation
Object-goal navigation (ObjectNav) requires an embodied agent to find an instance of a specified category in an unseen environment and stop near it.SuperMimic: Scaling Humanoid Whole-Body Control with One Differentiable World Model
Tracking large human-motion datasets has become the dominant route to general, expressive humanoid whole-body control, but scaling across many motions is expensive.VLM-Guided Contact Retargeting and Generative Partner Modeling for Humanoid-Human Interaction
Humanoid-human interaction requires robots to operate under severe partial observability: during close physical contact, the human partner is occluded, truncated, or outside the robot's field of…CoGaussian: Open-Vocabulary Gaussian-based Collaborative 3D Scene Understanding
Collaborative perception enables agents to retrieve the scene semantics and geometry beyond the field of view of any individual agent.MAPLE: Mondrian-Anchored Prior for Learning-free Indoor Exploration
Robots exploring unknown indoor environments must decide where to move while much of the environment remains unseen.SceneRig: An Agentic System for Simulation-Ready 3D Scene Reconstruction from Single Images
Simulation is a powerful tool for robotics, but building diverse, simulation-ready scenes at scale remains difficult.AgenticRoboRL: Bringing Coding-Agent Post-Training to Agentic Robotics
Agentic robotics systems combine planners with robot harnesses to perform complex manipulation tasks.Physical Canvas: A Vision Tactile World Model For Robot Policy Evaluation And Learning
Evaluating and post-training robot policies through physical interaction is costly and difficult to scale, motivating action-conditioned world models as interactive simulators.Planning under Noise with Neural Operators
Planning under uncertain control execution noise requires reliable feedback policies across diverse environments.Industrial ReMEmbR: Scaling Spatiotemporal Memory to Robot Fleets
Warehouse robot fleets continuously observe operational conditions, but preserving these observations as reusable semantic memory incurs substantial computation, communication, and storage costs.UniWALM: Unified World Action Language Model for Embodied Robot Control
Motivated by the human ability to integrate experience across language, perception, and action, we introduce UniWALM, a unified world-action-language model that learns video, action, and language in…Learning Adaptable Dexterous Skills via Hybrid Dexterous Mimicking
Dexterous multi-finger hands hold promise to unlock diverse skills like functional grasps, in-hand reorientation, and dynamic handover that the human-designed world assumes, yet existing learning…Joints, Camera, Action! Co-Generating 3D Motion and Video for Arbitrary Rigs
Video generation models can now depict remarkably realistic motion.