Search

Extended Kalman filter (EKF) is one of the most widely used Bayesian estimation methods in the optimal control area. Recent works on mobile robot control and transportation systems have applied various EKF methods, especially for localization. However, it is difficult to obtain adequate and reliable process-noise and measurement-noise models due to the complex and dynamic surrounding environments and sensor uncertainty. Generally, the default noise values of the sensors are provided by the manufacturer, but the values may frequently change depending on the environment. Thus, this paper mainly focuses on designing a highly accurate trainable EKF-based localization framework using inertial measurement units (IMUs) for the autonomous ground vehicle (AGV) with dead reckoning, with the goal of fusing it with a laser imaging, detection, and ranging (LiDAR) sensor-based simultaneous localization and mapping (SLAM) estimation for enhancing the performance. Convolution neural networks (CNNs), backward propagation algorithms, and gradient descent methods are implemented in the system to optimize the parameters in our framework. Furthermore, we develop a unique cost function for training the models to improve EKF accuracy. The proposed work is general and applicable to diverse IMU-aided robot localization models. [ABSTRACT FROM AUTHOR]

The World Health Organization has identified Alzheimer's disease (AD), the leading cause of dementia globally, as a public health priority. However, the complex multifactorial pathology of AD means that its etiology remains incompletely understood. Despite being recognized a century ago, incomplete knowledge has hindered the development of effective treatments for AD. Recent scientific advancements, particularly in induced pluripotent stem cell (iPSC) technology, show great promise in elucidating the fundamental mechanisms of AD. iPSCs play a dual role in regenerating damaged cells for therapeutic purposes and creating disease models to understand AD pathology and aid in drug screening. Nevertheless, as an emerging field, iPSC technology requires further technological advancement to develop effective AD treatments in the future. Thus, this review summarizes recent advances in stem cell therapies, specifically iPSCs, aimed at understanding AD pathology and developing treatments., (©The Author(s) 2024. Open Access. This article is licensed under a Creative Commons CC-BY International License.)