Results 101 to 110 of about 10,208 (177)
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
Enabling Stochastic Dynamic Games for Robotic Swarms
This paper scales stochastic dynamic games to large swarms of robots through selective agent modeling and variable partial belief space planning. We formulate these games using a belief space variant of iterative Linear Quadratic Gaussian (iLQG). We scale to teams of 50 agents through selective modeling based on the estimated influence of agents ...
Kamran Vakil, Alyssa Pierson
wiley +1 more source
Shape memory alloy wires exhibit thermally induced phase changes that generate actuation strain and resistance variations enabling self‐sensing. However, hysteretic electromechanical behavior complicates accurate state estimation. This paper presents an artificial in‐based self‐sensing method to reconstruct SMA actuator position in real time, achieving
Krunal Koshiya +2 more
wiley +1 more source
A modular eight‐legged robot exploits anisotropically oriented soft I‐beam backbones to transmit vibration from a single unbalanced‐mass actuator, producing frequency‐dependent multimodal gaits. A pseudo‐rigid‐body model enables high‐fidelity MuJoCo simulation, while Bayesian parameter identification and reinforcement learning yield robust control ...
Yiğit Yaman +4 more
wiley +1 more source
The Sci-Hub Ban in India: When Copyright Collides with Clinical Reality. [PDF]
Ghatak T, Mani UA.
europepmc +1 more source
Controlling Dynamical Systems Into Unseen Target States Using Machine Learning
Parameter‐aware next‐generation reservoir computing enables efficient, data‐driven control of dynamical systems across unseen target states and nonstationary transitions. The approach suppresses transient behavior while navigating system collapse scenarios with minimal training data—over an order of magnitude less than traditional methods.
Daniel Köglmayr +2 more
wiley +1 more source
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella +5 more
wiley +1 more source
Different types of abdominal wall endometriosis have different clinical features and surgical outcomes. [PDF]
Li M, Li H, Ji H, Liu C.
europepmc +1 more source
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury +2 more
wiley +1 more source

