Unmanned aerial vehicles (UAVs) do not collide with obstacles, generate a path in real-time, and must fly to the target point. The sampling-based rapidly exploring random tree (RRT) algorithm has the advantages of fast computation and low computational complexity. It is suitable for real-time path generation, but the optimal path cannot be guaranteed. Further, the direction of the flight and the minimum radius of rotation have not been taken into account for the characteristics of the UAVs. This work proposes a Dubins path-oriented RRT* algorithm, which applies the Dubins path to the RRT algorithm to consider the direction of flight and the minimum radius of rotation and improves optimality and convergence. The proposed algorithm sets the sample node as the target point, orients toward the Dubins path, and then generates a tree. To verify the performance of the proposed algorithm, it is compared with existing RRT algorithms. As a result of performance analysis, the proposed algorithm improved the path length by 14.87% and the calculation time by 82.36%. Finally, the algorithm’s performance is verified by applying the proposed algorithm to a fixed-wing UAV and performing a numerical analysis of the generated path.

This paper presents a novel control framework for enhancing the attitude stabilization of multirotor UAVs using Control Moment Gyros (CMGs) and a Disturbance Robust Drive Law (DRDL). Due to their lightweight and compact structure, multirotor UAVs are highly susceptible to disturbances such as wind, making it challenging to achieve stable attitude control using rotor thrust alone. To address this issue, we employ CMGs to provide robust attitude control and apply Fast Terminal Sliding Mode Control (FTSMC) to ensure fast and accurate convergence within a finite time. The combination of CMGs’ torque amplification capability with the DRDL enables the system to effectively avoid singularities and maintain stable control performance in the presence of disturbances. Simulation results demonstrate that the CMG-equipped hexarotor utilizing the DRDL rapidly converges to the target attitude despite external disturbances, while minimizing oscillations in both motor speed and gimbal movement. Additionally, compared to the pseudo-inverse control method, the proposed approach significantly improves singularity avoidance and disturbance mitigation. The proposed control framework enhances the stability and reliability of UAV operations and demonstrates its potential for high-performance control in challenging disturbance environments.

In this work, a sliding-mode-based attitude controller constrained with the angular rate for unmanned aerial vehicles (UAVs) is addressed to withstand conditions below the allowable maximum angular velocity of UAVs in order to avoid the possibility of structural failure and to operate UAVs safely. The sliding mode controller suggested in this work defines a new sliding surface, inherently having two equilibrium points. These equilibrium points are carefully inspected, and the stability of the system controlled by means of the proposed approach is also analyzed using Lyapunov stability theory. To highlight the angular-rate constrained attitude control technique, a three-dimensional path is constructed using the Dubins path technique, and three-axis attitude commands for UAV are also generated by augmenting the line-of-sight algorithm. Compared with conventional sliding mode control measures, the excellent performance of the suggested control algorithm has been demonstrated by conducting numerical simulations.