Results 141 to 150 of about 2,605,876 (309)

Comprehension categories and the semantics of type dependency

Theoretical Computer Science, 1993
A comprehension category is a functor \({\mathcal P} : \mathbb{E} \to \mathbb{B}^ \to\) such that (i) \(cod \circ {\mathcal P} : \mathbb{E} \to \mathbb{B}\) is a fibration, and (ii) \(f\) is cartesian in \(\mathbb{E}\) implies that \({\mathcal P}f\) is a pullback in \(\mathbb{B}\). Here \(\mathbb{B}^ \to\) is the arrow category of \(\mathbb{B}\), and \(
openaire   +2 more sources

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, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

Semantic-Guided Hierarchical Consistency Domain Adaptation for Open-Set Remote Sensing Scene Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Open-set domain adaptation (OSDA) aims to generalize cross-domain remote sensing scene classification by classifying unknown categories that exist in the target and not seen in the source domain.
Yang Zhao, Jiaqi Liang, Hancheng Ma, Pingping Huang, Yifan Dong, Jing Li   +5 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

The Neural Representations of Movement across Semantic Categories. [PDF]

J Cogn Neurosci, 2019
Borghesani V, Riello M, Gesierich B, Brentari V, Monti A, Gorno-Tempini ML.   +5 more
europepmc   +1 more source

Mutual Adaptation and Influence: Review of Latent Dynamics Models in Human–Robot Interaction

Advanced Robotics Research, EarlyView.
Robots are becoming better teammates by learning hidden patterns in how people act. This review covers how state‐of‐the‐art approaches leverage these patterns to help robots not only react but also anticipate and guide cooperation. Here, we synthesize a unifying framework for these approaches, classify and review existing works, and highlight key ...
Mason O. Smith, Sunny Amatya, Seyed Yousef Soltanian, Jonathan Bush, Wenlong Zhang   +4 more
wiley   +1 more source

DRIVE‐SAFE: Data‐Driven Robustness and Informed Validation for Evolving Specifications via Formal Evaluation

Advanced Robotics Research, EarlyView.
DRIVE‐SAFE evaluates learning‐based, black‐box autonomous driving policies against evolving temporal safety requirements using Signal Temporal Logic robustness metrics. It aggregates distributional robustness measures with domain‐informed weights to guide iterative retraining.
Kristy Sakano, Jianyu An, Dinesh Manocha, Huan Xu   +3 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

Online comprehension across different semantic categories in preschool children with autism spectrum disorder. [PDF]

PLoS One, 2019
Barone R, Spampinato C, Pino C, Palermo F, Scuderi A, Zavattieri A, Gulisano M, Giordano D, Rizzo R.   +8 more
europepmc   +1 more source

Flexible Sensors for Robotics Tactile Perception: A Review

Advanced Robotics Research, EarlyView.
Flexible tactile sensing for robotics is reviewed through four interconnected dimensions. Physical mechanisms include piezoresistive, capacitive, piezoelectric, triboelectric, iontronic, and optical sensing. Structural design includes bioinspired, defect‐based, and MEMS‐based tactile systems.
Yu Song, Ying Chen, Yihao Chen, Xue Feng
wiley   +1 more source