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.
Get the few papers worth your time in Robotics every morning.
Follow Robotics and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 119
ACG-WAM: World-Action Modeling via Action-Conditioned Geometric Latent Prediction
World action models jointly learn visual predictionand robot actions, providing a way to use observations ofscene evolution for policy learning.Autonomous Droplet Navigation via Model-Based Reinforcement Learning: Zero-Shot Transfer and Emergent Dynamics
Self-driving laboratories (SDLs) are transforming chemical and materials discovery through closed-loop automation, yet automated infrastructure for physical manipulation of soft, deformable matter…Mind the Refinement Gap: When Safe High-Level Robot Plans Produce Unsafe Executions
Language-enabled robot systems increasingly combine semantic-graph planning with temporal-logic safety monitors.A Passive AI System for Verifying Physical State on Automated Liquid Handlers
Automated liquid handlers execute digital protocols, but operators must assemble the deck and confirm that the physical setup matches the intended experiment.DeltaWorld: Physically Consistent Interactive World Simulators via Action-Conditioned Latent Increment Learning
Interactive world simulators can provide scalable environments for robot planning, policy training, and evaluation by predicting action consequences while reducing reliance on repeated physical…Who Went Where When on the Lunar Surface: Forensic Trajectory Analysis to Identify Byzantine Rovers
Future planetary surface missions are likely to involve multiple independently operated rovers sharing the same deployment region, raising the need to verify compliance with operational constraints…GeoScaffold: Learning Compact Geometric Latents via Reconstruction for Efficient Vision-Language Navigation
Recent vision-and-language navigation (VLN) systems increasingly adopt streaming Video-LLM policies that map egocentric RGB observations and instructions directly to low-level actions.AdaTempo: Learning Shared Relative Tempo from Demonstrations for Faster Robot Manipulation
Visuomotor policies trained via imitation learning often inherit the unnecessarily slow timing of teleoperated demonstrations.RoboChemGym: A Protocol-Driven Generative Simulation Framework for Long-Horizon Chemical Manipulation
Wet-lab experimentation serves as the gold standard for hypothesis verification in scientific discovery; yet it is inherently labor-intensive, costly, and safety-critical.RoboBridge: A Self-Evolving Embodied Agent Framework for Sim-to-Real Transfer
A key challenge in bringing embodied intelligence into the real world is transferring capabilities from simulation to reality and enabling agents to continually adapt after deployment.Around the World: Unified Learned Locomotion on a 270 g Continuous-Rotation Quadruped
Closed-loop learned locomotion is established on commercial quadrupeds but remains uncommon at the sub-kilogram scale.CSIR: Contextually and Socially Informed Robots for Efficient Person Goal Navigation
We address the Person Goal Navigation (PersonNav) problem, enabling robots to search for people under realistic constraints on information accessibility and language uncertainty.Proprioceptive Sketches as Long-Horizon Intent for Generative Action Policies
Generative robot policies predict short action chunks but lack explicit long-horizon intent.Localized Conformal Safety Monitoring with Vision-Language Models for Autonomous Driving
Monitoring planned driving trajectories requires accurately estimating the collision likelihood with actors whose motion is itself impacted by the ego motion.SimpleTouch: Can Vision-Language-Action Models Master Contact-Rich Manipulation Without Tactile Policy Pretraining?
Tactile sensing provides essential contact information for robotic manipulation, yet incorporating it into pretrained vision-language-action (VLA) models remains challenging.Skill2Real: Agentic Skill Learning for Zero-Shot Sim-to-Real Robot Manipulation
Transferring robotic skills from simulation to reality requires task knowledge that remains usable across differences in perception, dynamics, and embodiment.FUSEye: Training-Light Fisheye Detection with Overlapping Views and Zero-Initialized Adapters
Fisheye cameras give mobile robots a single-sensor, low-cost view of their surroundings, yet the COCO-pretrained detectors that practitioners routinely reuse fail on them: strong radial distortion…VIGOR: Zero-Shot Visual Generalization via Latent-Space Consistency in Model-Based Reinforcement Learning
Model-based reinforcement learning (MBRL) achieves strong sample efficiency by planning within learned latent dynamics, yet its performance degrades substantially under unseen visual distractions…ManiPhysicsBench: Physics-Based Assessment of Object Preservation in VLA Manipulation
Vision-language-action (VLA) models aim to perform diverse manipulation tasks, but task success in existing rigid-body benchmarks does not indicate whether they preserve objects.LOCUS: Landmark-Oriented Container Discrimination Using Spatial Graphs
As robots are increasingly deployed in unstructured, real-world environments, the ability to reason about complex spatial and semantic relationships among objects remains a fundamental challenge in…