Applied & Human-Centered · Computer Science & AI
Robotics
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4,418 papers, from 4 September 2026 to 5 November 2026: 4,418 arXiv preprints.
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EndoRSI: Physical-Evidence-Driven Recursive Improvement of Endoscopic Robot Policies
Artificial intelligence is beginning to automate scientific discovery, yet physical robot-policy research still relies on scientists and engineers to interpret experimental failures and decide how…Robot-WATCHDOG : failure detection through object-centric graph representation
Reliable real-time failure detection is critical for deploying learned robotic policies, yet defining failures explicitly is infeasible in open-world settings.ManeuverFlow: Maneuver Hypothesis Generation with Future Evidence for Trajectory Evaluation and Refinement in End-to-End Autonomous Driving
End-to-end planning in complex scenes must model diverse driving intentions and select the most appropriate trajectory using scene context and future risks.Reflect-VLA: Internalizing Reflective Guidance via Dual-Path On-Policy Self-Distillation for Autonomous Driving
Reinforcement Learning (RL) substantially improves planning performance in autonomous-driving Vision-Language-Action (VLA) models.A Local Agentic AI Framework to Generate Edge Case Scenarios for Safety Assurance
Generating edge case scenarios is crucial for training, testing and safety assuring autonomous systems.RESCUE: Is This Alarm Worth Acting On? Counterfactual Evaluation of VLA Runtime Monitors
Runtime failure monitors for robot policies are typically evaluated by how accurately they distinguish failed from successful executions.Beyond Successful Robot Demonstrations: Learning from Human Interactions and Modeling Failure Dynamics
Action-conditioned world models offer a promising foundation for generalist robotic intelligence by predicting the consequences of actions.MAGMA-Bench: Evaluating Long-Horizon Embodied Agents under Dynamic Tasks and Execution Failures
Long-horizon embodied agents must maintain task-relevant information, coordinate heterogeneous robots, and adapt their decisions as execution unfolds.Probabilistic Ship Trajectory Forecasting using Transformer Models on AIS Data
Anticipation of vessel trajectories is an essential task when navigating at sea.ATHLETE: Learning Reactive Humanoid Tennis via Trajectory-Guided Motion Matching
Humanoid tennis requires reactive whole-body coordination under rapidly changing ball dynamics, yet collecting task-specific motion-capture demonstrations that cover diverse approach states, contact…RARA: Robust Policy Fine-Tuning through Retrieval-Anchored Representation Alignment for Robotic Manipulation
Pre-trained robot policies, such as Vision-Language-Action (VLA) models, provide a strong foundation for generalist robotic manipulation, but adapting them to new tasks with only a few…JitterVLA: A Replay Benchmark for Motion Quality in VLA-Driven Human-Robot Manipulation
Vision-language-action (VLA) policies issue sparse targets whose arrival at the robot controller is delayed and irregular, so a reasonable predicted action can still produce abrupt motion near people.AutoBio+: Benchmarking Dexterous Manipulation with Dynamic Experimental Phenomena in Realistic Laboratories
Automating biological laboratories requires robots to perform dexterous tool interactions under realistic visual conditions while handling dynamic experimental phenomena, presenting significant…Cooperative Aerial Transportation of a Payload with a Sliding Cable Attachment
This paper presents a dual-quadrotor hook- suspended transport system for cooperative aerial manipulation of a payload that is not rigidly attached to a fixed point along the cable.Towards a Unified Taxonomy of Agricultural Harvesting Technologies: Linking Physical Interaction, Automation, and Selectivity
Harvesting technologies have evolved from conventional mechanized systems based on bulk mechanical interaction toward increasingly automated and robotic systems capable of perception…LAPT-Scale: Scaling Embodied Policies with Latent Action Pre-Training on Human Videos
Scaling generalist robotic policies is limited by the high cost of collecting embodied interaction data.SmolWAM: A Latent World-Action Model for Robotic Manipulation on Edge Devices
World-action models (WAMs) predict a robot's actions together with the observations those actions will produce.MARGoS: A Configuration-Driven Platform for Reproducible MARL Experiments in ARGoS
Multi-agent reinforcement learning (MARL) has become a prominent research direction, particularly within collective robotics, where the ARGoS simulator is widely used to study emergent swarm behavior.When LiDAR Fades, Radar Takes Over: LiDAR Reliability-Aware Adaptive Localization Under Airborne Obscurants
LiDAR-inertial odometry (LIO) is widely used for real-time localization and mapping, but its reliability can degrade substantially in subterranean environments affected by smoke, dust, and other…Dream to Remember: Continual Steering of Generalist Robot Policies with World Models
Generalist robot policies are trained with imitation learning and are bounded by the quality and coverage of their demonstrations.