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 219
Rethinking Learned Occupancy in Autonomous Active Mapping with Observation-Gated Filtering
Autonomous 3D active mapping requires a space robot to choose where to sense while building the geometry needed for navigation.Online, Reachability-Aware, Sampling-Based Motion Planning
Sampling-Based Model-Predictive Control (MPC) algorithms are a flexible class of controllers used for navigation on a wide range of robotic systems.DeCAL: Towards Physically-Grounded Dexterous Vision-Language-Action Models via Contact-Aware Latent Co-Imagination
Dexterous manipulation involves contact-rich and fine-grained interactions with the physical world, posing significant challenges for existing vision-language-action (VLA) models due to severe…Proxy Policy Steering
Generalist robot policies carry broad manipulation priors from large-scale data, but specializing them to a new task remains the deployment bottleneck.TANGO: Humanoid Navigation in Cluttered Environments with a Whole-Body Vision-Language-Action Model
We study the problem of navigating cluttered indoor environments with a humanoid robot.No Free Checker: A Survey of Verifiers for Robot Policies
A verifier for robot policies reads a candidate behavior and returns a score for how well it did, used both to evaluate vision-language-action policies and to train them.AccelMPC: High-Rate, Low-Power FPGA-Accelerated Model Predictive Control for Tiny Drones
Unlocking the potential of tiny aerial robots requires order of magnitude improvements in the performance of embedded edge control.Networked Admissibility-Preserving Control for Directed Safe Coordination
This paper addresses safety-critical coordination for scalar agents whose distributed commands are implemented through constrained physical-input dynamics.A Decade of Bayesian Optimization for Controller Tuning and Robot Learning: Tutorial, Review, and Future Prospects
In the past decade, Bayesian optimization (BO) has emerged as a powerful and adaptable framework for automatic controller tuning and robot learning.Decision-Focused Active Learning for Scale-Aware Critical-Materials Recovery
Choosing a recovery process for scale-up requires connecting laboratory results with product requirements, process costs, and scale effects.Fast Constraint Extraction for Corrective Control under STL Specifications via Logical Dependency Tracking
Ensuring the satisfaction of Signal Temporal Logic (STL) specifications under uncertainty is challenging, as reachability-based monitoring provides guarantees but does not indicate how to restore…Unthrottling the Tanh Jacobian in SAC: A Negative Result on Bang-Bang Control and MetaDrive
Soft Actor-Critic (SAC) represents a continuous policy as an unbounded Gaussian that is squashed by tanh.Actuator Dynamics Curricula for Narrow-Viability Tasks in Legged Robot Learning
Reinforcement learning has produced capable controllers across a broad range of legged-robot tasks, but a subset of these tasks fail to converge under standard training: those for which most…Agentic AI-enabled Semantic Commissioning of a Cognitive Digital Twin for Reconfigurable Manufacturing
Rapid bespoke commissioning of the Cognitive Digital Twin (CDT) is a major challenge in reconfigurable manufacturing.Contextual Observer Grounding: Evaluating Situated Spatial Reasoning in Vision-Language Models
Reasoning over language instructions in embodied tasks such as robotics often requires understanding spatial relations from a speaker's situated perspective.Noisy-Space Policy Gradient for Diffusion Policies in Offline Reinforcement Learning
Diffusion policies offer a powerful and expressive parameterization for continuous control.Distributed Dexterous Manipulation with Spatially Conditioned Multi-Agent Transformers
Distributed Dexterous Manipulation (DDM) is a novel paradigm that presents significant control challenges due to high action-space redundancy, inter-robot cooperation, and dynamic object-robot…Joint-Conditioned Stereo Surface Reasoning for Interaction Field Estimation
Predicting hand--object interaction fields requires locating the nearest object-surface point for each hand joint, often from small and partially occluded image regions.Mind the Phase: Effective Rank and Representation Health in Legged Locomotion
Reinforcement learning has become the leading paradigm in legged locomotion, enabling complex behaviors from backflips to parkour through massively parallel simulation.GIFT: Goal-Injected Fine-Tuning for Efficient Manipulation Policy Adaptation
Compared with relying solely on initial observations and language instructions, predicting goal images with generative models as high-level visual guidance can significantly enhance the robustness…