This paper investigates the distributed leader-following formation control problem for
multiple nonholonomic wheeled mobile robots via a bioinspired neurodynamic approach. To …

Simulation plays a pivotal role in providing safely reproducible scenarios to evaluate the
ever-advancing domain of computer science and robotics. It was an essential part of the …

Traditional deep learning approaches for prediction of future trajectory of multiple road
agents rely on knowing information about their past trajectory. In contrast, this work utilizes …

This article focuses on the event-triggered (ET) fuzzy tracking control for uncertain state
constrained strict-feedback systems with unknown control directions. A novel nonlinear …

In this paper, we investigate a neural adaptive formation control problem for underactuated
unmanned surface vehicles (USVs). Considering the limitation of communication distance …

This paper studies the consensus control of nonlinear impulsive distributed parameter multi-
agent systems (IDPMASs), whose dynamic behavior depends on time and space. First, to …

This paper focuses on the control of spherical formation for multi-agent systems with double-
integrator dynamics in three-dimensional space. To achieve the desired formation pattern on …

A novel multi‐input multi‐output adaptive control strategy applied to the combined active
front steering (AFS) and direct yaw moment control (DYC) system is proposed in this paper …

In this work, we propose a learning based neural model that provides both the longitudinal
and lateral control commands to simultaneously navigate multiple vehicles. The goal is to …

Siamese networks have recently attracted much attention due to balancing accuracy and
speed in tracking. However, most Siamese trackers emphasize how to learn target features …