Results 141 to 150 of about 7,645,086 (295)

A Relation-Specific Entropy-Based Ensemble Approach for Knowledge Graph Embedding

IEEE Access
Knowledge Graph Embedding (KGE) aims to represent entities and relationships from knowledge graphs (KGs) in vector spaces. Existing KGE methods often focus narrowly on specific relation patterns or employ ensemble weights based on the prediction scores ...
Hwawoo Jeon, Yoonseob Lim, Yong Suk Choi
doaj   +1 more source

Embedding Logical Queries on Knowledge Graphs

, 2018
Learning low-dimensional embeddings of knowledge graphs is a powerful approach used to predict unobserved or missing edges between entities. However, an open challenge in this area is developing techniques that can go beyond simple edge prediction and handle more complex logical queries, which might involve multiple unobserved edges, entities, and ...
William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec   +4 more
openaire   +3 more sources

Durability of Soft Pneumatic Actuators: A Review and Benchmarking Protocol

Advanced Robotics Research, EarlyView.
Lack of durability is a key challenge hindering the broad scale adoption of soft pneumatic actuators (SPAs) in automation industries. This review provides a comprehensive overview of existing research on SPA durability, introduces a standardized durability benchmarking protocol to consolidate the testing of SPAs, and outlines promising directions for ...
Dickson Chiu Yu Wong, Yucheng Luo, Rob Bernardus Nicolaas Scharff   +2 more
wiley   +1 more source

Towards leveraging explicit negative statements in knowledge graph embeddings

Web Semantics
Knowledge Graphs are used in various domains to represent knowledge about entities and their relations. In the vast majority of cases, they capture what is known to be true about those entities, i.e., positive statements, while the Open World Assumption ...
Rita T. Sousa, Catia Pesquita, Heiko Paulheim   +2 more
doaj   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley   +1 more source

Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling

Advanced Robotics Research, EarlyView.
A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang, Ganesh Arivoli, Huzaifa Unjhawala, Luning Bakke, Radu Serban, Dan Negrut   +5 more
wiley   +1 more source

An inductive knowledge graph embedding via combination of subgraph and type information. [PDF]

Sci Rep, 2023
Liu H, Chen Y, He P, Zhang C, Wu H, Zhang J.   +5 more
europepmc   +1 more source

Knowledge graph and text jointly embedding

, 2014
We examine the embedding approach to reason new relational facts from a large-scale knowledge graph and a text corpus. We propose a novel method of jointly em-bedding entities and words into the same continuous vector space.
Zhen Wang, Jianwen Zhang, Zheng Chen, Jianlin Feng   +3 more
core   +1 more source

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Advanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source