This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, RandLA-Net, and VoxelRCNN— on a Flash Lidar dataset ...

Abstract: This article addresses high-precision trajectory tracking for fully actuated hexarotor unmanned aerial vehicles (UAVs) subject to model uncertainty and external disturbances. To exploit the ...

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.

Multi-robot systems are increasingly deployed in complex, dynamic environments such as environmental monitoring, industrial automation, and search-and-rescue missions. The coordination of such systems ...

Today on CNN10: We'll learn how the ongoing government shutdown could reduce the amount of flights at some of the country's busiest airports. Then, we'll get an update on Typhoon Kalmagi, the ...

Institute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China ...

Abstract: This paper investigates the problem of tracking morphologically similar targets for nonlinear systems and proposes an adaptive-gain reinforcement iterative learning control (AG-RILC) scheme.

A new study published in Nature Communications provides evidence that the brain chemical dopamine plays a sophisticated, dual role in how we learn, influencing both our fast, effortful thinking and ...

This project presents a complete workflow for cone detection in Formula Student Driverless scenarios using deep learning. It demonstrates how to use MATLAB® and Simulink® for data preparation and ...