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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 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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 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A Capability and Skill Model for Heterogeneous Autonomous Robots
Luis Miguel Vieira da Silva, Aljosha Köcher, Alexander Fay · 2022-09-22 · via cs.RO updates on arXiv.org

Teams of heterogeneous autonomous robots become increasingly important due to their facilitation of various complex tasks. For such heterogeneous robots, there is currently no consistent way of describing the functions that each robot provides. In the field of manufacturing, capability modeling is considered a promising approach to semantically model functions provided by different machines. This contribution investigates how to apply and extend capability models from manufacturing to the field of autonomous robots and presents an approach for such a capability model.

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