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 157
Find Something You Can't Do: Agentic Real-World Reinforcement Learning for Self-Improving VLA Models
Vision--language--action (VLA) models provide strong priors for robotic manipulation but are typically deployed as frozen policies, unable to improve from their own failures.Fiber-Normalized Manipulability and Determinant Proxies: Intrinsic Redundancy Optimization Across and Within Task Fibers
This work establishes that determinant-based manipulability is an exact objective for fixed-task redundancy optimization, despite its dependence on task coordinates and the choice of task-space…Direction-Scale Decomposition in Action Representation: Rethinking What to Tokenize for Vision-Language-Action Models
Action representation plays a central role in discrete-token vision-language-action (VLA) learning but remains underexamined.Online Sim-to-Real Adaptation via Closed-Loop System Modeling
Sim-to-real transfer has made substantial progress, but can still produce controllers that remain stable and functional on hardware while suffering from degraded tracking accuracy due to residual…Fly, Drive, Reconfigure: A Modular Reconfigurable Aerial-Ground Platform for Field Operations
Heterogeneous robot teams distribute complementary capabilities across specialized agents, but their physical roles and capacities typically remain fixed throughout a mission.Robots That Take Initiative: A Framework for Building and Evaluating Proactive Robots
Effective robot assistance beyond narrow roles and repetitive tasks requires robots to be proactive - to decide what needs to be done rather than waiting to be told.Koopman-Accelerated Model-Based Diffusion for Real-Time Robot Control
Conventional model-based diffusion (MBD) achieves effective trajectory optimization by leveraging noise annealing.Streaming-WAM: Action-Conditioned World-Action Model for Asynchronous Robot Manipulation
World action models (WAMs) that use future visual prediction at inference time incur substantial generation costs.A Field-Deployable GNSS-based Navigation Stack for Outdoor Mobile Robots
Outdoor robots require more than an accurate receiver and a path-tracking law: the navigation system must preserve geometric consistency from geographic waypoints to actuator commands, expose…RoboRecover: Benchmarking Robot Policy Recovery under Execution Deviations
Robot-policy benchmarks increasingly cover diverse tasks and preset out-of-distribution conditions, but typically evaluate complete trajectories from predefined initial states.ActGaze: Learning Action-Grounded Gaze through Counterfactual Visual Interventions for High-Precision Manipulation
Current Vision-Language-Action (VLA) models often struggle with high-precision robotic manipulation.TactileStep: Sole Tactile Learning for Regulating Foot-Terrain Interaction in Humanoid Locomotion
Humanoid parkour policies can traverse various terrains, but task completion may mask challenges of harsh landings, edge contacts, and unstable stance contacts.Echo in the Steps: Learning Perceptive Humanoid Parkour with Gated Memory
While recent advances in perceptive locomotion have enabled humanoid robots to traverse structured terrains, agile parkour in highly discontinuous environments remains an open challenge.Sim-to-Real Aware End-to-End Learning Environment for Micromobility
While end-to-end autonomous driving systems show promise, their application to micromobility vehicles is hindered by simulators failing to capture specific kinematics, such as differential drives…AquaMend: Minimal Re-probing and Conditional Rollback for Latent-Belief Failures in Embodied Agents
Physical changes or sensing errors can invalidate embodied agents' task-relevant beliefs.ReVNM: Learning-Based Visual Navigation from a Remote Camera
Visual Navigation Models (VNMs) enable robots to navigate from egocentric visual observations without geometric localization and planning, but long-range navigation still requires pre-built maps.CrossSafe: Towards Cross-Embodiment Latent Safety Filters
Cross-embodiment learning has shown that a single model, such as a vision-language-action (VLA) model, can learn state representations and manipulation skills that can be applied across…CALM: Current Aligned Link Manipulation for Single Arm Oversized Object Lifting
Most robots manipulate objects solely with their end effectors, whereas humans flexibly leverage different body parts, such as the forearm and elbow, especially when handling oversized objects.Outcome-Sensitive Motion Search for Impact-Aware Dexterous Catching
Skilled humans can catch fast-moving objects softly by coordinating interception, velocity matching, and follow-through to mitigate impact.CAMP: Cooperative Arm-Hand Motion Planning in Constrained Spaces
Coordinated arm-hand motion planning is fundamental to dexterous robotic manipulation in complex and constrained environments.