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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Back on Track: Deployment-time Policy Improvement via World Model Planning
State-of-the-art visuomotor policies are increasingly capable of executing complex tasks, yet can fail during deployment in ways they cannot predict or recover from on their own.RoboSpan: Learning Modular Coordination Policies for High-DoF Whole-Body Mobile Manipulation with Teleoperation
Whole-body mobile manipulation suffers from two fundamental challenges: inherent motion heterogeneity across locomotion, arm, and hand modules, and progressive error accumulation over long-horizon…Cracking Mobile Manipulation: From Failure Diagnosis to Agentic Robot System
Recent vision-language-action (VLA) models have shown strong performance on local robot manipulation, yet their success does not readily translate to long-horizon mobile manipulation.ForceBench: Benchmarking Force Integration for Robotic Manipulation
Force feedback provides vision-language-action (VLA) policies with physical observations that can guide action selection and execution.PolyMorph: Learning Locomotion Policy for Cross-Embodiment Adaptation
Reinforcement learning has enabled robust locomotion for legged robots, but learned policies are typically tied to a specific robot morphology and require additional engineering when the number of…Instruction-Conditioned Motion Control for Robotic Arms: Language-to-Code Decomposition and Reinforcement Learning
Instruction-Conditioned Motion Control (ICMC) separates parameter specification, instruction generation, and code synthesis for language-driven robot control, making execution outcomes traceable to…F2A-ObjectNav: An Adaptive Agentic Architecture for Object-Goal Navigation
Object-goal navigation requires an embodied agent to explore an unfamiliar environment, identify a target object, navigate toward candidate instances, and reliably determine whether the observed…E2DRL: End-to-End Differentiable Reinforcement Learning for 3D Obstacle Avoidance in Quadruped Robots
Differentiable reinforcement learning shows strong promise for robot policy learning, but its application to legged locomotion has remained limited to blind walking or simulated 2D tasks.Eye, Robot: Learning Expressive Gaze Dynamics via a VLM-Guided Transformer-VAE
Gaze coordinates attention in human interaction through coupled eye, head, and eyelid motion.Accelerating VLA Inference with Perturbation Informed Execution
Action-chunking vision-language-action (VLA) models predict sequences of future robot actions.ACRO: Actor-Critic Rollout Orchestration
Executing a vision-language-action (VLA) policy involves deciding when to continue an attempt and when to intervene to improve its chances of success.Uncertainty-Driven Self-Play for Robust Multi-Agent Driving Policies
Learning robust driving policies that generalize beyond their training domain remains a central challenge in motion planning.What Happens to the Goal? Distinct Failures of Policy Alignment in Goal Misgeneralization
Goal misgeneralization is a common failure mode in which an agent behaves competently out of distribution but does not pursue the intended goal.HyperLoop: Hyperspectral-Assisted Loop Closure Detection in 3D-SLAM for Planetary Exploration
Autonomous navigation of planetary rovers is challenged by visually repetitive, featureless terrain.One-shot Human Video-Guided Adaptation for Vision-Language-Action Models
Vision-language-action (VLA) models have recently achieved remarkable progress by leveraging large-scale robot datasets and foundation models for general-purpose robot manipulation.Coordi-pi: Coordination-Aware Dual-Hand Action Representation for Bimanual Dexterous Manipulation
Vision-language-action (VLA) models have shown strong potential for general-purpose robotic manipulation, but extending them to bimanual dexterous manipulation introduces a high-dimensional and…Mixed-Reality Feedback Control: Towards Blending of Control and Digital Twinning
Technologies, such as co-simulation, in particular, digital twins (DTs) are used for comprehensive and reliable prototyping, verification and validation (V&V) of control systems.Refine Actions If Needed: Adaptive Action Chunk Refinement for Robot Manipulation
Computationally lightweight manipulation policies predict executable actions with low inference latency, but prediction errors can limit task success.Design and Characterization of a Unified Continuum Robot Actuation Platform
Continuum robots enable dexterous access to confined spaces in applications such as minimally invasive surgery and industrial inspection.Learning from Demonstrations meets Symbolic Control - A Supervisory Control Architecture for Formal Certification of Learned Motion
Dynamical system (DS)-based learning from demonstration generates flexible robot motions, but existing guarantees rely on certificate generation to obtain formal guarantees of safety and goal…