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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Newest papers, page 184
2nd Place Solution to the HANDS 2026 Workshop Challenge-Dexterous Grasp Motion Track: Single-Shot Trajectory Warping for Grasp Motion Generation
This report describes our 2nd place solution to the HANDS 2026 workshop challenge (Dexterous Grasp Motion track) in conjunction with ECCV 2026.Skel-WAM: A Hand-Skeleton-Conditioned World Action Model for Human-to-Robot Manipulation Transfer
Robot demonstrations are expensive to collect and often provide limited distributional coverage of task variations.2D GauSS-MI: Efficient Active Scene Reconstruction with Balanced Visual and Geometric Quality
Active reconstruction requires efficient active view selection to achieve high-quality reconstruction within limited onboard computational resources.SABER: Learning Attention-based Semantic Affordance for Legged Locomotion
Perceptive legged locomotion has advanced rapidly by integrating terrain geometry into learned policies, yet the integration of terrain meaning remains sparse: a pipe, a patch of grass, or a fragile…Tilt as a Certified Resource: Preserving Motor Wrench-Rate Authority on Articulated Multirotors
Fully-actuated multirotor aerial vehicles must not only track nominal wrenches but retain the "readiness" to modulate them rapidly under disturbances.A High-Payload Wall-Climbing Robot Using Passive Bistable Suction Cups
Wall-climbing robots capable of scaling vertical surfaces could help automate hazardous or labor intensive tasks such as window washing, inspection, maintenance, and construction.Potential-Field Action Representation for Reinforcement Learning in Contact-Rich Manipulation
Model-free reinforcement learning can acquire contact-rich robotic manipulation skills through trial-and-error interaction, but it often requires the policy to learn both task strategy and low-level…CounterPlay: Counterfactual Post-Training for Self-Play Driving Policies
Self-play in high-throughput simulators yields driving policies with robust closed-loop performance, but improvement per unit of simulation diminishes as training scales.Towards Fine-Grained Object Manipulation: SAM3-Guided Visuomotor Policy with Persistent Memory Learning and Focused Visual Conditioning
Fine-grained object (FO) manipulation requires robots to distinguish a specified FO from visually similar objects and execute actions reliably despite scene distractors.SynthDemo-RL: Breaking the Zero-Reward Barrier in VLA Adaptation with LLM-Guided Synthetic Demonstrations
Fine-tuning Vision-Language-Action (VLA) models commonly relies on human teleoperation demonstrations, while reinforcement learning (RL) with sparse binary rewards faces an exploration challenge…Outcome-Conditioned End-Effector Geometry Across Vision-Language-Action Policies
Vision-language-action (VLA) policies solve the same manipulation task through different action interfaces, but task success alone does not establish whether their physical executions agree.RAYA: Learning Where and When to Intervene for Robot Recovery
A robot can predict failure and still be unable to prevent it.NeuRIO: A Streaming Neural Estimator for Zero-Shot Sim-to-Real Multi-Robot Relative Inertial Odometry
We present NeuRIO, a streaming neural estimator for anchor-free 6-DoF relative inertial odometry using only identified inter-robot bearings, ranges, and IMU measurements.AgenticSwarm: Semantic Perception and Adaptive Task Allocation for Heterogeneous Multi-UAV Missions
Multi UAV missions in complex environments require the system to understand both the surrounding scene and the intent of a human operator while maintaining feasible task allocation as mission…A Novel Path-Tracking Algorithm for Automated Tractor-Trailer Forward and Backward Maneuvers
Fully autonomous tractor--trailer systems are increasingly deployed in logistics, agriculture, and industrial environments, where precise and robust path-tracking capabilities are essential.ZeroTouch: Tactile-Supervised Visual Contact Estimation for Contact-Rich Manipulation
Reliable robotic grasping benefits from estimating the evolving physical interaction and selecting a grasp-dependent compression target.Visual Proactivity: Enhancing Human-Robot Collaboration Through Intent Communication
As robots transition from performing repetitive tasks to collaborating with humans, understanding human intent becomes crucial to effective interaction.When Should Robots Intervene? Balancing Engagement and Intrusiveness in Human-Robot Interaction
Designing effective Human-Robot Interaction in task-oriented settings requires carefully balancing user engagement with socially acceptable levels of robot intrusiveness.Sandwich-Residuals: Parameter-Efficient Test-time Adaptation of World Models
Latent world models enable planning by predicting the effects of actions in a learned representation space, but their predictions can become unreliable when test-time conditions differ from training.Understanding Engagement and Intrusiveness in Assistive Human-Robot Interaction Using Individual Traits
Robot assistance is particularly crucial in unfamiliar tasks, where users must understand task requirements while coordinating with the robot.