Abstract: In this study, to improve the accuracy of path tracking in intelligent vehicles, we propose an intelligent vehicle path-tracking control method based on improved model predictive control ...
Abstract: The rapid increase in the volume of data generated from connected devices in industrial Internet of Things paradigm, opens up new possibilities for enhancing the quality of service for the ...
Abstract: In this paper, the direct adaptive neural control is proposed for a class of uncertain nonaffine nonlinear systems with unknown nonsymmetric input saturation. Based on the implicit function ...
Abstract: Remote sensing image scene classification, which aims at labeling remote sensing images with a set of semantic categories based on their contents, has broad applications in a range of fields ...
Abstract: The structural similarity image quality paradigm is based on the assumption that the human visual system is highly adapted for extracting structural information from the scene, and therefore ...
Abstract: A novel surgical palpation probe installing a miniature 6-axis force/torque (F/T) sensor is presented for robot-assisted minimally invasive surgery. The 6-axis F/T sensor is developed by ...
Abstract: Link Aggregation allows parallel point-to-point links to be used as if they were a single link and also supports the use of multiple links as a resilient load-sharing interconnect between ...
Abstract: Realtime multi-person 2D pose estimation is a key component in enabling machines to have an understanding of people in images and videos. In this work, we present a realtime approach to ...
Abstract: This letter describes Fields2Cover, a novel open source library for coverage path planning (CPP) for agricultural vehicles. While there are several CPP solutions nowadays, there have been ...
Abstract: A linear/nonlinear active disturbance rejection control (ADRC) switching control (SADRC) strategy for permanent magnet synchronous motors (PMSMs) is proposed in this article to integrate the ...
Abstract: The spatial information of Electroencephalography (EEG) is essential for emotion recognition model to learn discriminative feature. The convolutional networks and recurrent networks are the ...