Results 101 to 110 of about 350,580 (291)
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
Advanced Robotics Research, EarlyView.BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source
The Information-Flow Approach to Ontology-Based Semantic Integration
, 2010 In this article we argue for the lack of formal foundations for ontology-based semantic alignment. We analyse and formalise the basic notions of semantic matching and alignment and we situate them in the context of ontology-based alignment in open-ended ...
Kalfoglou, Yannis, Schorlemmer, Marco
core
PENERAPAN TEKNIK SEMANTIC MAPPING DALAM PEMBELAJARAN KANJI [PDF]
, 2015 Tujuan dalam penelitian ini adalah untuk mengetahui peguasaan huruf kanji mahasiswa yang diterapkan teknik Semantic Mapping dan teknik pencatatan biasa, untuk mengetahui perbedaan yang signifikan penguasaan huruf kanji antara mahasiswa yang diterapkan ...
Yeni, -
core
Advanced Robotics Research, EarlyView.Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Terrain-aware semantic mapping for cooperative subterranean exploration. [PDF]
Front Robot AI, 2023 Miles MJ, Biggie H, Heckman C.
europepmc +1 more source
Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models
Advanced Robotics Research, EarlyView.A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki +2 more
wiley +1 more source
Probabilistic Semantic Mapping for Autonomous Driving in Urban Environments. [PDF]
Sensors (Basel), 2023 Zhang H +5 more
europepmc +1 more source
Computer Graphics ForumAbstractWe present an automated technique for computing a map between two genus‐zero shapes, which matches semantically corresponding regions to one another. Lack of annotated data prohibits direct inference of 3D semantic priors; instead, current state‐of‐the‐art methods predominantly optimize geometric properties or require varying amounts of manual ...
Luca Morreale +3 more
openaire +3 more sources
3D Mapping with Semantic Knowledge [PDF]
, 2006 A basic task of rescue robot systems is mapping of the environment. Localizing injured persons, guiding rescue workers and excavation equipment requires a precise 3D map of the environment. This paper presents a new 3D laser range finder and novel scan matching method for the robot Kurt3D [9].
Andreas Nüchter +5 more
openaire +1 more source