There is an increasing demand for using Unmanned Aerial Vehicle (UAV), known as drones,
in different applications such as packages delivery, traffic monitoring, search and rescue …

This article presents a framework that extends a rapidly exploring random tree (RRT)
algorithm to plan the motion for a wheeled robot under kinodynamic constraints. Unlike …

This work designed a disturbance-observer-based nonlinear sliding mode surface controller
(SMC) and validated the controller using a simulated PX4-conducted quadcopter. To …

In this study, a novel end-to-end path planning algorithm based on deep reinforcement
learning is proposed for aerial robots deployed in dense environments. The learning agent …

In this article, a real-time interactive time-optimal trajectory planning (TOTP) strategy is
proposed for aircraft slung-load systems, in which the practical performance is guaranteed …

In recent years, the rapid development in contemporary technology has brought nano
quadcopters with high agility. This paper presents a new differential flatness-based Single …

In autonomous and mobile robotics, one of the main challenges is the robust on-the-fly
perception of the environment, which is often unknown and dynamic, like in autonomous …

In this paper, a novel Virtual State-feedback Reference Feedback Tuning (VSFRT) and
Approximate Iterative Value Iteration Reinforcement Learning (AI-VIRL) are applied for …

In multi-agent settings, game theory is a natural framework for describing the strategic
interactions of agents whose objectives depend upon one another's behavior. Trajectory …

A general control system tracking learning framework is proposed, by which an optimal
learned tracking behavior called 'primitive'is extrapolated to new unseen trajectories without …