Results 51 to 60 of about 78,709 (143)

An LLM-Based Digital Twin for Optimizing Human-in-the Loop Systems

2024 IEEE International Workshop on Foundation Models for Cyber-Physical Systems & Internet of Things (FMSys)
The increasing prevalence of Cyber-Physical Systems and the Internet of Things (CPS-IoT) applications and Foundation Models are enabling new applications that leverage real-time control of the environment. For example, real-time control of Heating, Ventilation and Air-Conditioning (HVAC) systems can reduce its usage when not needed for the comfort of ...
Hanqing Yang 0007, Marie Siew, Carlee Joe-Wong   +2 more
openaire   +2 more sources

Human-in-the-Loop Control Framework for Robot-Mediated Error Augmentation Training Based on Muscle Synergy Assessment

IEEE Transactions on Neural Systems and Rehabilitation Engineering
Robot-mediated error augmentation (EA) offers a promising paradigm for enhancing motor adaptation by amplifying movement errors rather than compensating for them.
Xiao Li, Aiguo Song, Jianwei Lai, Wenbin Zhang, Kui Qian, Junhui Wu, Ying Shen   +6 more
doaj   +1 more source

Personalized Image Generation via Human-in-the-loop Bayesian Optimization

CoRR
Imagine Alice has a specific image $x^\ast$ in her mind, say, the view of the street in which she grew up during her childhood. To generate that exact image, she guides a generative model with multiple rounds of prompting and arrives at an image $x^{p*}$.
Rajalaxmi Rajagopalan, Debottam Dutta, Yu-Lin Wei, Romit Roy Choudhury   +3 more
openaire   +2 more sources

Bayesian Preference Elicitation: Human-In-The-Loop Optimization of An Active Prosthesis

CoRR
Tuning active prostheses for people with amputation is time-consuming and relies on metrics that may not fully reflect user needs. We introduce a human-in-the-loop optimization (HILO) approach that leverages direct user preferences to personalize a standard four-parameter prosthesis controller efficiently.
Sophia Taddei, Wouter Koppen, Eligia Alfio, Stefano Nuzzo, Louis L. Flynn, María Alejandra Díaz, Sebastian Rojas-Gonzalez, Tom Dhaene, Kevin De Pauw, Ivo Couckuyt, Tom Verstraten   +10 more
openaire   +2 more sources

Concurrent Adaptive Control for a Robotic Leg Prosthesis via a Neuromuscular-Force-Based Impedance Method and Human-in-the-Loop Optimization

Applied Sciences
This paper proposes an adaptive human–robot concurrent control scheme that achieves the appropriate gait trajectory for a robotic leg prosthesis to improve the wearer’s comfort in various tasks.
Ming Pi
doaj   +1 more source

Power Management of a Wind-Powered Microgrid Based on Qualitative Needs

Energies
Power management strategies for microgrids are typically designed around quantitative performance metrics such as cost, efficiency, and reliability. While effective in many settings, these approaches often do not fully account for qualitative, human ...
Maryam Yaghoubirad, John Hall
doaj   +1 more source

Human-in-the-loop: Real-time Preference Optimization

Optimization with preference feedback is an active research area with many applications in engineering systems where humans play a central role, such as building control and autonomous vehicles. While most existing studies focus on optimizing a static user utility, few have investigated its closed-loop behavior that accounts for system transients.
Wang, Wenbin, Xu, Wenjie, Jones, Colin N.   +2 more
openaire   +2 more sources

Leveraging Sub-Optimal Data for Human-in-the-Loop Reinforcement Learning

International Joint Conference on Autonomous Agents and Multiagent Systems
To create useful reinforcement learning (RL) agents, step zero is to design a suitable reward function that captures the nuances of the task. However, reward engineering can be a difficult and time-consuming process. Instead, human-in-the-loop (HitL) RL approaches allow agents to learn reward functions from human feedback.
Calarina Muslimani, Matthew E. Taylor
openaire   +4 more sources

Optimizing Exoskeleton Assistance: Muscle Synergy-Based Actuation for Personalized Hip Exoskeleton Control

Actuators
Exoskeleton robots hold promising prospects for rehabilitation training in individuals with weakened muscular conditions. However, achieving improved human–machine interaction and delivering customized assistance remains a challenging task.
Yehao Ma, Dewei Liu, Zehao Yan, Linfan Yu, Lianghong Gui, Canjun Yang, Wei Yang   +6 more
doaj   +1 more source

Human-in-the-Loop Optimization of Transcranial Electrical Stimulation at the Point of Care: A Computational Perspective. [PDF]

Brain Sci, 2022
Arora Y, Dutta A.
europepmc   +1 more source