N Wang, X Li, K Zhang, J Wang, D Xie - Machines, 2024 - mdpi.com
Autonomous driving in unstructured environments is crucial for various applications, including agriculture, military, and mining. However, research in unstructured environments …
This work is concerned with the vulnerability of a network industrial control system to cyber- attacks, which is a critical issue nowadays. This is because an attack on a controlled process …
L Yu, H Wu, C Liu, H Jiao - Sensors, 2022 - mdpi.com
Thanks to their strong maneuverability and high load capacity, car-like robots with non- holonomic constraints are often used in logistics to improve efficiency. However, it is difficult …
Model Predictive Control (MPC) algorithms typically use the classical L 2 cost function, which minimises squared differences of predicted control errors. Such an approach has …
This work has two objectives. Firstly, it describes a novel physics-informed hybrid neural network (PIHNN) model based on the long short-term memory (LSTM) neural network. The …
Q Wang, L Jiang, X Sun, J Zhao, Z Deng, S Yang - Sensors, 2022 - mdpi.com
In this article, we present an efficient coding scheme for LiDAR point cloud maps. As a point cloud map consists of numerous single scans spliced together, by recording the time stamp …
The paper proposes a new real-time motion planning technique for an autonomous mobile robot that is able to find a collision-free path and a corresponding time-optimal trajectory …
This study presents the development and analysis of a technique for planning the autonomous vehicle (AV) motion references using sequential optimization. The method …
In recent years, autonomous electric vehicles (A-EVs) have attracted the attention of academia and industry. In urban mobility, this topology requires consensus to control …