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cs.RO updates on arXiv.org

FineCog-Nav: Integrating Fine-grained Cognitive Modules for Zero-shot Multimodal UAV Navigation DENALI: A Dataset Enabling Non-Line-of-Sight Spatial Reasoning with Low-Cost LiDARs SENSE: Stereo OpEN Vocabulary SEmantic Segmentation Continual Hand-Eye Calibration for Open-world Robotic Manipulation PLAF: Pixel-wise Language-Aligned Feature Extraction for Efficient 3D Scene Understanding GaussianFlow SLAM: Monocular Gaussian Splatting SLAM Guided by GaussianFlow GIST: Multimodal Knowledge Extraction and Spatial Grounding via Intelligent Semantic Topology $π_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities R3D: Revisiting 3D Policy Learning Vision-Based Safe Human-Robot Collaboration with Uncertainty Guarantees Benchmarking Classical Coverage Path Planning Heuristics on Irregular Hexagonal Grids for Maritime Coverage Scenarios NEAT-NC: NEAT guided Navigation Cells for Robot Path Planning HRDexDB: A Large-Scale Dataset of Dexterous Human and Robotic Hand Grasps ADAPT: Benchmarking Commonsense Planning under Unspecified Affordance Constraints An Intelligent Robotic and Bio-Digestor Framework for Smart Waste Management Efficient closed-form approaches for pose estimation using Sylvester forms World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems A Nonasymptotic Theory of Gain-Dependent Error Dynamics in Behavior Cloning CooperDrive: Enhancing Driving Decisions Through Cooperative Perception SpaceMind: A Modular and Self-Evolving Embodied Vision-Language Agent Framework for Autonomous On-orbit Servicing HiVLA: A Visual-Grounded-Centric Hierarchical Embodied Manipulation System UMI-3D: Extending Universal Manipulation Interface from Vision-Limited to 3D Spatial Perception Towards Multi-Object-Tracking with Radar on a Fast Moving Vehicle: On the Potential of Processing Radar in the Frequency Domain Beyond Conservative Automated Driving in Multi-Agent Scenarios via Coupled Model Predictive Control and Deep Reinforcement Learning Failure Identification in Imitation Learning Via Statistical and Semantic Filtering A Dynamic-Growing Fuzzy-Neuro Controller, Application to a 3PSP Parallel Robot Vision-Language-Action Jump-Starting for Reinforcement Learning Robotic Agents A Mechanistic Analysis of Sim-and-Real Co-Training in Generative Robot Policies ESCAPE: Episodic Spatial Memory and Adaptive Execution Policy for Long-Horizon Mobile Manipulation Evolvable Embodied Agent for Robotic Manipulation via Long Short-Term Reflection and Optimization Chain of Uncertain Rewards with Large Language Models for Reinforcement Learning RadarSplat-RIO: Indoor Radar-Inertial Odometry with Gaussian Splatting-Based Radar Bundle Adjustment RobotPan: A 360$^\circ$ Surround-View Robotic Vision System for Embodied Perception Diffusion Sequence Models for Generative In-Context Meta-Learning of Robot Dynamics GeoVision-Enabled Digital Twin for Hybrid Autonomous-Teleoperated Medical Responses 4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview Multi-modal panoramic 3D outdoor datasets for place categorization Learning Probabilistic Responsibility Allocations for Multi-Agent Interactions Solving Physics Olympiad via Reinforcement Learning on Physics Simulators StarVLA-$α$: Reducing Complexity in Vision-Language-Action Systems Grounded World Model for Semantically Generalizable Planning SCORP: Scene-Consistent Multi-agent Diffusion Planning with Stable Online Reinforcement Post-Training for Cooperative Driving Agentic Driving Coach: Robustness and Determinism of Agentic AI-Powered Human-in-the-Loop Cyber-Physical Systems AffordSim: A Scalable Data Generator and Benchmark for Affordance-Aware Robotic Manipulation Efficient Emotion-Aware Iconic Gesture Prediction for Robot Co-Speech Minimal Embodiment Enables Efficient Learning of Number Concepts in Robot Learning to Forget -- Hierarchical Episodic Memory for Lifelong Robot Deployment 3D-Anchored Lookahead Planning for Persistent Robotic Scene Memory via World-Model-Based MCTS EmbodiedGovBench: A Benchmark for Governance, Recovery, and Upgrade Safety in Embodied Agent Systems Federated Single-Agent Robotics: Multi-Robot Coordination Without Intra-Robot Multi-Agent Fragmentation Robust Adversarial Policy Optimization Under Dynamics Uncertainty BridgeSim: Unveiling the OL-CL Gap in End-to-End Autonomous Driving AffordGen: Generating Diverse Demonstrations for Generalizable Object Manipulation with Afford Correspondence Genie 4D: Semantic-Prior-Guided 4D Dynamic Scene Reconstruction RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies ProGAL-VLA: Grounded Alignment through Prospective Reasoning in Vision-Language-Action Models PhysInOne: Visual Physics Learning and Reasoning in One Suite C$^2$T: Captioning-Structure and LLM-Aligned Common-Sense Reward Learning for Traffic--Vehicle Coordination WOMBET: World Model-Based Experience Transfer for Robust and Sample-efficient Reinforcement Learning Accelerating Transformer-Based Monocular SLAM via Geometric Utility Scoring 3D-VCD: Hallucination Mitigation in 3D-LLM Embodied Agents through Visual Contrastive Decoding Action Images: End-to-End Policy Learning via Multiview Video Generation Towards Generalizable Robotic Manipulation in Dynamic Environments General-purpose LLMs as Models of Human Driver Behavior: The Case of Simplified Merging Uncertainty, Vagueness, and Ambiguity in Human-Robot Interaction: Why Conceptualization Matters IROSA: Interactive Robot Skill Adaptation using Natural Language Online Navigation Planning for Long-term Autonomous Operation of Underwater Gliders Optimized Human-Robot Co-Dispatch Planning for Petro-Site Surveillance under Varying Criticalities MerNav: A Highly Generalizable Memory-Execute-Review Framework for Zero-Shot Object Goal Navigation From Instruction to Event: Sound-Triggered Mobile Manipulation Self-Organizing Dual-Buffer Adaptive Clustering Experience Replay (SODACER) for Safe Reinforcement Learning in Optimal Control Enhanced-FQL($λ$), an Efficient and Interpretable RL with novel Fuzzy Eligibility Traces and Segmented Experience Replay LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving Learning to Plan, Planning to Learn: Adaptive Hierarchical RL-MPC for Sample-Efficient Decision Making Target-Bench: Can Video World Models Achieve Mapless Path Planning with Semantic Targets? Robust Verification of Controllers under State Uncertainty via Hamilton-Jacobi Reachability Analysis Towards Deploying VLA without Fine-Tuning: Plug-and-Play Inference-Time VLA Policy Steering via Embodied Evolutionary Diffusion Volumetric Ergodic Control RoboTAG: End-to-end Robot Configuration Estimation via Topological Alignment Graph TwinOR: Photorealistic Digital Twins of Dynamic Operating Rooms for Embodied AI Research Multimodal Diffusion Forcing for Forceful Manipulation X-Diffusion: Training Diffusion Policies on Cross-Embodiment Human Demonstrations Hierarchical DLO Routing with Reinforcement Learning and In-Context Vision-language Models Flow with the Force Field: Learning 3D Compliant Flow Matching Policies from Force and Demonstration-Guided Simulation Data AFFORD2ACT: Affordance-Guided Automatic Keypoint Selection for Generalizable and Lightweight Robotic Manipulation HAMLET: Switch your Vision-Language-Action Model into a History-Aware Policy TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance Multi-Modal Manipulation via Multi-Modal Policy Consensus AutoDrive-R$^2$: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Driving Constrained Decoding for Safe Robot Navigation Foundation Models FCBV-Net: Category-Level Robotic Garment Smoothing via Feature-Conditioned Bimanual Value Prediction PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Driving LLM-based Realistic Safety-Critical Driving Video Generation Scalable Multi-Task Learning through Spiking Neural Networks with Adaptive Task-Switching Policy for Intelligent Autonomous Agents Learning to Play Piano in the Real World Scalable Unseen Objects 6-DoF Absolute Pose Estimation with Robotic Integration Sixth-Sense: Self-Supervised Learning of Spatial Awareness of Humans from a Planar Lidar Curriculum-based Sample Efficient Reinforcement Learning for Robust Stabilization of a Quadrotor Generative Models and Connected and Automated Vehicles: A Survey in Exploring the Intersection of Transportation and AI Convex Hulls of Reachable Sets
Tagging Real-World Scenarios for the Assessment of Autonomous Vehicles
Erwin de Gelder, Olaf Op den Camp · 2020-12-02 · via cs.RO updates on arXiv.org

The development of Autonomous Vehicles (AVs) has made significant progress in the last years. An essential aspect in the development of AVs is the assessment of quality and performance aspects of the AVs, such as safety, comfort, and efficiency. Among other methods, a scenario-based approach has been proposed. With scenario-based testing, the AV is subjected to a collection of scenarios that represent real-world situations. The collection of scenarios needs to cover the variety of what an AV can encounter in real traffic. As a result, many different scenarios are considered, that are grouped into so-called scenario categories. We propose a method for defining the scenario categories using a system of tags, where each tag describes a particular characteristic of a scenario category. There is a balance between having generic scenario categories - very specific set of scenarios, while for another system one might be interested in a set of scenarios with a high variety. To accommodate this, tags are structured in trees. The different layers of the trees can be regarded as different abstraction levels. Next to presenting the method for describing scenario categories using tags, we will illustrate the method by showing applicable trees of tags using concrete examples in the Singapore traffic system. Trees of tags are shown for the vehicle under test, the dynamic environment (e.g., the other road users), the static environment (e.g., the road layout), and the environmental conditions (weather and lighting conditions). Few examples are presented to illustrate the proposed method for defining the scenario categories using tags.