arXiv AI
Aug 5
Principles of Robot Autonomy
arXiv:2608. 03496v1 Announce Type: cross Abstract: Autonomous robots are moving rapidly from research labs into everyday life - on roads, in the air, in warehouses, and in space.
Robotics and embodied AI
Manipulation, locomotion, sim-to-real transfer and autonomous driving: learning systems that have to survive physics.
Hugging Face Trending Papers
Aug 5
Image Classification Using CNN-QNN Hybrid Model with Optimized Correlated Features
We propose a method to optimize the correlation among convolutional neural network (CNN) features that are used as inputs to quantum neural network (QNN) to enhance image classification accuracy. Unlike prior approaches that employ orthogonal decomposition as preprocessing, we intentionally introduce correlated features that are more physically compatible with QNN.
Hugging Face Trending Papers
Aug 4
SiMDex: Mining Similar Egocentric Videos for Cross-Embodiment Dexterous Manipulation
Recent years have witnessed an explosive trend of scaling ego-centric human videos for robot manipulation, yet it remains unclear which data actually benefits dexterous manipulation. We present SiMDex, a similarity-based data mining framework that casts human data selection for VLA post-training in dexterous manipulation as a recommendation problem.
Hugging Face Trending Papers
Aug 4
Shaping Wind-Tunnel Airflow for Unmanned Aerial Vehicles using Online Learning
The development and testing of advanced aerial robots require experiments in controlled environments with tailored airflow profiles. This paper presents an online learning algorithm for controlling the complex airflow field in a multi-fan vertical wind tunnel.
Hugging Face Trending Papers
Aug 4
UniNav: A Unified World-Action Diffusion Model for Visual Navigation
Image-goal visual navigation is a fundamental capability for embodied agents. Existing navigation policies efficiently predict waypoint trajectories but lack visual foresight, while navigation world models can anticipate future observations but often require costly planning rollouts.
Hugging Face Trending Papers
Aug 4
Multimodal Plant Root Phenotyping with Integration of 3D Skeleton Extraction and Language Analysis
Plant root phenotyping is fundamental to understanding below-ground structures, optimizing crop management, and improving agricultural sustainability. This paper presents a multimodal robotic AI framework that integrates 3D skeleton extraction with language-guided reasoning for interpretable and data-efficient root analysis.
arXiv Machine Learning
Aug 4
LOCUS-DT: Localization via Observation-Conditioned Uncertainty Scoring with Digital Twins
arXiv:2608. 00406v1 Announce Type: cross Abstract: Accurate indoor localization is essential for emerging applications in robotic navigation and search and rescue.
arXiv Machine Learning
Aug 4
GraRe: Grasp Candidate Re-Ranking for Frozen 6-DoF Grasp Detectors
arXiv:2608. 00946v1 Announce Type: cross Abstract: Existing 6-DoF grasp detectors typically rank grasp candidates by detector confidence.
arXiv Machine Learning
Aug 4
Scoring Rules! Statistical and Strategic Alignment for Text Evaluation Metrics
arXiv:2608. 01423v1 Announce Type: cross Abstract: Reference-based text evaluation metrics, which are widely used to assess natural language generation systems, score a candidate response by comparing it with a reference response.
arXiv Machine Learning
Aug 4
Rapid Embodiment Adaptation for Quadrupedal Locomotion
arXiv:2608. 01506v1 Announce Type: cross Abstract: Humans readily adapt their movements as their bodies change through aging, injury, or load carrying, but learning-based robot policies often break when hardware properties shift.
arXiv Machine Learning
Aug 4
Policy Optimality Measurement for Multi-Vehicle Decision-Making: From Extrinsic Indicators to Intrinsic Quality
arXiv:2608. 01133v1 Announce Type: new Abstract: Evaluating Multi-Agent Reinforcement Learning (MARL) policies in autonomous driving fundamentally relies on extrinsic statistical indicators (e.
arXiv Machine Learning
Aug 4
CoWAM: Coordination Contracts for Selective Policy Intervention with WAMs
arXiv:2608. 02578v1 Announce Type: cross Abstract: World Action Models (WAMs) augment robot policies with action-conditioned predicted futures, but a plausible future alone does not justify changing the action that a bimanual policy would execute.
arXiv Machine Learning
Aug 4
Human-Centered Reflections on Care Robots: A Comparative Study of Caregiver Perspectives
arXiv:2608. 02411v1 Announce Type: cross Abstract: Care robots are increasingly being introduced into healthcare settings, raising important questions about their acceptance and ethical implementation.
arXiv Machine Learning
Aug 4
Foundations of Reinforcement Learning and Control:Connections and New Perspectives
arXiv:2608. 02433v1 Announce Type: new Abstract: Reinforcement learning and control theory are two adjacent scientific fields that focus on optimizing the controller of unknown dynamical systems using feedback.
arXiv Machine Learning
Aug 4
From Digital to Physical Reservoir Computing: Co-Optimizing Soft Robotic Reservoirs via Dynamics Matching
arXiv:2608. 00484v1 Announce Type: cross Abstract: Soft robotic substrates are promising for Physical Reservoir Computing (PRC) because their compliant nonlinear dynamics can provide temporal memory, high-dimensional state transformations, and efficient inference.
arXiv Machine Learning
Aug 4
Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning
arXiv:2608. 02034v1 Announce Type: new Abstract: Multi-step returns accelerate reward propagation in off-policy reinforcement learning, but couple the evaluation of each decision to the suboptimal logged actions that follow it, inducing a pessimistic bias that grows with the horizon.
arXiv Machine Learning
Aug 4
ActionCache: Training-Free Acceleration for Vision-Language-Action Models with Action Caching and Refinement
arXiv:2607. 06370v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising approach for generalizable robotic manipulations.
arXiv Machine Learning
Aug 4
When Replanning Becomes the Bottleneck: Budgeted Replanning for Embodied Agents
arXiv:2608. 01428v1 Announce Type: cross Abstract: Embodied agents replan frequently to recover from execution drift, partial observability, and coordination hazards, but each LLM-based replanning call can consume an accumulated textual context that grows over time and across agents.
arXiv Machine Learning
Aug 4
Towards General Language-Conditioned Latent Safety Filters
arXiv:2608. 00315v1 Announce Type: cross Abstract: Robot policies are becoming increasingly general, with vision-language-action (VLA) models enabling a single policy to execute diverse tasks specified in natural language.
arXiv Machine Learning
Aug 4
Fairness Auditing: Lower Bounds on Company Manipulation
arXiv:2608. 00568v1 Announce Type: new Abstract: Fairness audits are increasingly mandated in high-stakes applications such as hiring, lending, and automated decision-making.