Results 51 to 60 of about 35,533,713 (263)

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

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

Performance Evaluation in Single or Multi-Cluster C-RAN Supporting Quasi-Random Traffic [PDF]

Journal of Communications Software and Systems, 2020
In this paper, a cloud radio access network (C-RAN) is considered where the remote radio heads (RRHs) are separated from the baseband units (BBUs). The RRHs in the C-RAN are grouped in different clusters according to their capacity while the BBUs form a ...
Iskanter-Alexandros Chousainov, Ioannis Moscholios, Alexandros Kaloxylos, Michael Logothetis   +3 more
doaj  

Resilient Cloud Network Mapping with Virtualized BBU Placement for Cloud-RAN

, 2016
Cloud Radio Access Network (C-RAN) will improve mobile radio coordination and resource efficiency by allowing baseband processing unit (BBU) functions to be virtualized and centralized, i.e., deployed in a BBU hotel.
Colman Meixner, Carlos, Mukherjee, B., Gustavo B. Figueiredo, Massimo Tornatore, Figueiredo, G. B., Matteo Fiorani, Tornatore, M., Colman-Meixner, Carlos, Carlos Colman-Meixner, Biswanath Mukherjee, Figueiredo, Gustavo B., Mukherjee, Biswanath, Fiorani, Matteo,, TORNATORE, MASSIMO, Fiorani, Matteo, Colman-Meixner, C.   +15 more
core   +1 more source

Task‐Oriented Path Planning Towards Autonomous Sensor Network Deployment in Rainforest Canopies

Advanced Robotics Research, EarlyView.
An informative path planner for drone‐based deployment of wireless sensor networks in rainforest canopies is presented, addressing key challenges in large‐scale biodiversity monitoring. By integrating canopy surface detection with connectivity‐aware sampling under strict flight constraints, the approach enables efficient and reliable aerial sensor ...
Rita Santos Raminhos, Salua Hamaza
wiley   +1 more source

Fog Computing as an Enabler for Immersive Media: Service Scenarios and Research Opportunities

IEEE Access, 2019
Immersive media services, such as augmented reality and virtual reality (AR/VR),a 360-degree video, and free-viewpoint video (FVV), are popular today. They require massive data storage, ultrahigh computing power, and ultralow latency.
Dongho You, Tung V. Doan, Roberto Torre, Mahshid Mehrabi, Alexander Kropp, Vu Nguyen, Hani Salah, Giang T. Nguyen, Frank H. P. Fitzek   +8 more
doaj   +1 more source

Technical Feasibility Study of Autonomous Field Robot‐Based on‐the‐go Assessment of Soil Nutrients Using Ion‐Sensitive Field‐Effect Transistors

Advanced Robotics Research, EarlyView.
Autonomous field robots equipped with ISFET‐based sensors enable rapid, spatially resolved soil nutrient analysis directly in the field. An automated system based on the BoniRob platform is presented for standardized on‐site extraction and measurement of key macronutrients and soil pH.
Vadim Riedel, Stefan Hinck, Edgar Peiter, Arno Ruckelshausen   +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

Service Orchestrator in Cloud RAN based Edge Cloud

, 2018
International audienceFifth generation of mobile networks (5G) is designed to introduce a multitude of new services which require higher processing resources and lower latency. Cloud Radio Access Network (Cloud RAN) is one of the most promising solutions
Rejeb, Sonia, Ben, Agoulmine, Nazim, Chabbouh, Olfa, Baliosian, Javier   +3 more
core   +3 more sources

End-to-End Energy Efficiency Evaluation of 5G Networks in Dense Urban and Rural Scenarios Using Empirical Modeling and Monte Carlo Simulation

Applied Sciences
This paper provides a comprehensive end-to-end evaluation of the energy efficiency of three key fifth-generation mobile (5G) Radio Access Network (RAN) architectures: Distributed RAN (D-RAN), Centralized RAN (C-RAN), and Cloud C-RAN.
Bhuvaneshwar Doorgakant, Tulsi Pawan Fowdur, Mobayode O. Akinsolu   +2 more
doaj   +1 more source