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 34
Labference: Benchmarking the Reasoning-Action Connection in Robotic Laboratories
Realizing Embodied AI for Science requires robots to translate experimental goals into reliable physical procedures, reducing hazardous and repetitive human work while generating evidence for…Reward-Guided RRT* for Budgeted Task and Motion Planning
Robotic missions involving spatially distributed tasks often require jointly selecting rewarding locations and planning feasible motions under limited travel budgets.VisGeo-PipeTrack: A Visual Geometric Servo Control Framework with MPC-RCAPID Control for UAV-Based Dynamic Pipes Tracking
While unmanned aerial vehicles (UAVs) are increasingly deployed for pipeline inspection, prevailing research predominantly assumes static pipes.EmbodiedLab: Benchmarking Embodied Agents That Act to Know
Embodied agents are expected to accomplish real-world goals by deciding for themselves how and when to interact with their surroundings.MATE-BT: A Behavior-Tree-Based Framework for Hierarchically Decentralized Mission Autonomy in Heterogeneous Multi-Robot Teams
Multi-robot teams executing predefined missions must adapt to runtime changes and sustain mission management despite robot failures.Model-Aware Generation of Safety-Critical Scenes for Robust End-to-End Driving via Distilled Planner Surrogates
End-to-end driving models perform well on standard benchmarks but collide frequently in safety-critical scenarios.RoKON: Efficient and Adaptive Data-Enabled Predictive Control for Robotic Manipulation
Data-enabled predictive control has recently emerged as a promising control paradigm, enabling a transparent optimal-control formulation without the need to learn an explicit dynamics model.DEX-PHD: A Dexterous Portable Handheld Device for Multimodal Data Collection
Existing manipulation data collection methods typically offer either accurate robot-state acquisition through kinematic-chain-based teleoperation or convenient, portable operation through…Enhancing Deep Reinforcement Learning for Robotic Motion Planning via Task Decomposition
Obstacle-aware robotic manipulation can require substantial interaction data when deep reinforcement learning policies are trained from scratch.High-resolution tactile observation makes hidden racket-control mechanisms learnable
Experts can master fine hand-object manipulation skills, yet limited conscious perception of rapid tactile interactions hinders their ability to articulate the underlying control mechanisms.Preemptive Instruction Following with Resumption
Long-horizon embodied navigation may be interrupted by a higher-priority instruction before the current task sequence is complete.Distributed Predictive Flocking for a Swarm of Miniature Vibration-Driven Robots in a Confined Arena
Coordinating many miniature robots in a confined arena, with no leader, central planner, or global map, is a core challenge for swarm robotics.RoboDoctor: Training-Free Recursive Self-Improvement for Robot Policies
Generalist robot policies and language-model agents provide complementary capabilities, but completing a task also requires adapting their use to the consequences of physical interaction.Context-Aware Generation and Modulation of Expressive Motion Behavior using Multimodal Foundation Models
Expressive robot motion positively impacts human-robot interaction by improving user engagement, likability, or task performance.Robot-Aligned 3D Gaussian Splatting for Precise Reaching with Wrist-Camera VLA Policies
Efficient robotic data collection remains a major bottleneck for vision-language-action (VLA) policy learning, especially for tasks requiring accurate end-effector positioning and camera-action…From Language to Drives: A Multimodal Framework for Aligning Autonomous Robots with Human Purposes
This work explores a multimodal approach to the alignment of the behavior of open-ended learning autonomous robots with human purposes through the use of large language models as cultural enablers.Revisiting Direct Control: A Field Evaluation of Sensor Fusion Efficacy in Teleoperating Full-Scale Autonomous Vehicles via Bird's Eye View
In autonomous driving, robot teleoperation serves as a critical safety fallback mechanism, requiring operators to assume direct control in the event of system failure.Adapt for Planning, Not just Prediction: Optimistic Test-Time World Model Adaptation
Latent world models are typically pre-trained offline and kept frozen at test time, so planning with them can degrade under distribution shift.VPR-Space: A Benchmark for Visual Place Recognition in Space Analog Domains
Visual Place Recognition (VPR) is an important means for loop closure detection in visual Simultaneous Localization and Mapping (SLAM).Environment Edits as a Corrective Signal for Reward Learning
Robot corrections allow people to adjust a robot's behavior, but a single correction changes many features.