This paper addresses a local minima problem for multiple unmanned aerial vehicles (UAVs) in the process of collision avoidance by using the artificial potential field method, thereby enabling UAVs to avoid the obstacle effectively in 3-D space. The main contribution is to propose a collision avoidance control algorithm based on the virtual structure and the “leader–follower” control strategy in 3-D space that can avoid the obstacle effectively and then track the motion target. The three UAVs constitute the regular triangular formation as the control object, the virtual leader flight trajectory as the expected path, the obstacles as the simplified cylinders, and the artificial potential fields around them as approximately spherical surfaces. The attractive force of the artificial potential field can guide the virtual leader to track the target. At the same time, the follower tracks the leader to maintain the formation flight. The effect of the repulsive force can avoid the collision between the UAVs and arrange the followers such that they are evenly distributed on the spherical surface. Moreover, the follower’s specific order and position are not required. The collision path of the UAV formation depends on the artificial potential field with the two composite vectors, and every UAV may choose the optimal path to avoid the obstacle and reconfigure the regular triangular formation flight after passing the obstacle. The effectiveness of the proposed collision avoidance control algorithm is fully proved by simulation tests. Meanwhile, we also provide a new concept for multi-UAV formation avoidance of an obstacle.

Fixed-Wing UAV Formation Control Design With Collision Avoidance Based on an Improved Artificial Potential Field

The dramatic increase in the capabilities and availability of autonomous ground and aerial tools introduces safety and security challenges, particularly in protecting strategic infrastructures. In ...

Path Planning for Multiple Targets Interception by the Swarm of UAVs based on Swarm Intelligence Algorithms: A Review

To enhance the mission success rate, the multi-agent system (MAS) often adopts a formation form to shuttle over complex terrain. Compared with obstacle avoidance in other multi-agent coordinated missions, multi-agent formation (MAF) obstacle avoidance is more challenging because agents must both avoid obstacles and subsequently return to their intended positions in the original formation at a uniform speed. Aiming at the three-dimensional complex obstacle environment, the fluid methodology is extended to the application of the formation issue for the first time. In this paper, an MAF obstacle avoidance framework built upon model-based interfered fluid dynamical system (MIFDS), which is the most representative algorithm in fluid methodology, is proposed. The proposed MIFDS is modified to be more in accordance with the kinematic performance of agents than traditional IFDS by introducing the kinematic model and constraints. Moreover, on the basis of MIFDS and the virtual leader formation structure, a novel original fluid speed adjustment strategy in MIFDS, which is the core to solve the formation issue, is designed to balance obstacle avoidance and formation reconfiguration. Finally, receding horizon control is introduced to further guarantee the performance of obstacle avoidance and motion safety. Simulations are used to demonstrate the effectiveness of the proposed method.

Formation Obstacle Avoidance: A Fluid-Based Solution

Collision avoidance control for formation flying of multiple spacecraft using artificial potential field

Unmanned aerial vehicle use continues to increase, including operating beyond line of sight in unknown environments where the vehicle must autonomously generate a trajectory to safely navigate. In this article, we develop a trajectory generation algorithm for vehicles with second-order dynamics in unknown environments with bounded wind disturbances in which the vehicle only relies on its on-board distance sensors and communication with other vehicles to navigate. The proposed algorithm generates smooth trajectories and can be used with high-level planners and low-level motion controllers. The algorithm computes a maximum safe cruise velocity for the vehicle in the environment and guarantees that the trajectory does not violate the vehicle's thrust limitation, sensor constraints, or user-defined clearance radius around other vehicles and obstacles. Additionally, the trajectories are guaranteed to reach a stationary goal position in finite time given a finite number of bounded obstacles. Simulation results demonstrate the algorithm properties through two scenarios. First, a quadrotor navigating through a moving obstacle field to a goal position and, second, multiple quadrotors navigating into a building to different goal positions.

Reactive Trajectory Generation for Multiple Vehicles in Unknown Environments With Wind Disturbances

This paper considers the artificial potential field method combined with rotational vectors for a general problem of multi-unmanned aerial vehicle (UAV) systems tracking a moving target in dynamic three-dimensional environment. An attractive potential field is generated between the leader and the target. It drives the leader to track the target based on the relative position of them. The other UAVs in the formation are controlled to follow the leader by the attractive control force. The repulsive force affects among the UAVs to avoid collisions and distribute the UAVs evenly on the spherical surface whose center is the leader-UAV. Specific orders or positions of the UAVs are not required. The trajectories of avoidance obstacle can be obtained through two kinds of potential field with rotation vectors. Every UAV can choose the optimal trajectory to avoid the obstacle and reconfigure the formation after passing the obstacle. Simulations study on UAV are presented to demonstrate the effectiveness of proposed method.

/pdf/uav-formation-control-design-with-obstacle-avoidance-in-39apuhdh5g.pdf

UAV formation control design with obstacle avoidance in dynamic three-dimensional environment

This paper considers a problem of coordination formation control for multiple unmanned vehicles based on the behavioral control and virtual structures in three-dimensional space. The repulsive forces effect among unmanned vehicles to avoid collision with others and move them to the balance points on the spherical surface whose center is the virtual leader. The unmanned vehicles do not have specific identities or roles within the formation. The proposed method does not require specific orders or positions of the unmanned vehicles. The formation can transform automatically when unmanned vehicles enter or exit the formation. This paper also proposes a technique for avoiding obstacles based on the behavioral structure. In this technique, when an unmanned vehicle gets close to an obstacle, while moving toward its target, two kinds of potential fields with rotational vectors are applied to lead the unmanned vehicle to avoid the obstacle. Simulations are also given to verify the effectiveness of theoretical results.

Coordinated formation control design with obstacle avoidance in three-dimensional space

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UAV formation control design with obstacle avoidance in dynamic three-dimensional environment

Coordinated formation control design with obstacle avoidance in three-dimensional space