Ground Target Tracking and Collision Avoidance for UAV Based Guidance Vector Field

This paper focuses on ground-moving target tracking of an unmanned aerial vehicle (UAV) in the presence of static obstacles and moving threat sources. Due to a UAV is restricted by airspace restrictions and measurement limitations during flight, we derive a dynamic path planning strategy by generating guidance vector filed combined Lyapunov vector field with collision avoidance potential function to track target in standoff distance loitering pattern, and resolved collision avoidance, simultaneously. This method relies only on the current information of the UAV and target, and generates a single-step route plan in realtime. Its performance is simple, efficient, and fast and have low computational complexity. The results of numerical simulation verify the effectiveness of the tracking and collision avoidance process of the UAV.

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Adaptive Dynamic Path Planning Algorithm for Interception of a Moving Target

International Journal of Mobile Computing and Multimedia Communications ◽

10.4018/jmcmc.2013070102 ◽

2013 ◽

Vol 5 (3) ◽

pp. 19-33

Author(s):

H. H. Triharminto ◽

A.S. Prabuwono ◽

T. B. Adji ◽

N. A. Setiawan

Keyword(s):

Path Planning ◽

Dynamic Condition ◽

Cylindrical Shape ◽

Moving Target ◽

C Language ◽

Dynamic Path Planning ◽

Planning Algorithm ◽

Aerial Vehicle ◽

Dynamic Path ◽

Path Planning Algorithm

Most of the 3D curve path planning is used to build static path planning. For intercepting of a moving target, the path planning has to be set in a dynamic condition. L+Dumo algorithm which is based on curve is used to intercept a moving target. In the real situations, the Unmanned Aerial Vehicle (UAV) has possibility to intercept a moving target from all direction. It is assumed that environment of the UAV is in 3D Euclidean Space. It means that the UAV has to adapt for all quadrants for interception of a moving target. This research develops a path planning algorithm which enhances the previous L+Dumo algorithm to encounter the possibility quadrants. The enhancement would be simulated in C++ language to determine the accuracy of the algorithm. The simulation is conducted using one UAV and one moving target with random obstacles of cylindrical shape in between both objects. The result shows that the system accuracy is 81.0876%, a level which is able to encounter all possibility quadrants.

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Unmanned aerial vehicle dynamic path planning in an uncertain environment

Robotica ◽

10.1017/s0263574714000514 ◽

2014 ◽

Vol 33 (3) ◽

pp. 611-621 ◽

Cited By ~ 12

Author(s):

Min Yao ◽

Min Zhao

Keyword(s):

Path Planning ◽

Unmanned Aerial Vehicle ◽

Optimal Path ◽

Current Position ◽

Direction Angle ◽

Dynamic Path Planning ◽

Aerial Vehicle ◽

Dynamic Path ◽

Rolling Optimization ◽

Feedback Algorithm

SUMMARYAn unmanned aerial vehicle (UAV) dynamic path planning method is proposed to avoid not only static threats but also mobile threats. The path of a UAV is planned or modified by the potential trajectory of the mobile threat, which is predicted by its current position, velocity, and direction angle, because the positions of the UAV and mobile threat are dynamically changing. In each UAV planning path, the UAV incurs some costs, including control costs to change the direction angle, route costs to bypass the threats, and threat costs to acquire some probability to be destroyed by threats. The model predictive control (MPC) algorithm is used to determine the optimal or sub-optimal path with minimum overall costs. The MPC algorithm is a rolling-optimization feedback algorithm. It is used to plan the UAV path in several steps online instead of one-time offline to avoid sudden and mobile threats dynamically. Lastly, solution implementation is described along with several simulation results that demonstrate the effectiveness of the proposed method.

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Fast Convergent Lyapunov Vector Field Guidance for Standoff Target Tracking

2019 Chinese Control And Decision Conference (CCDC) ◽

10.1109/ccdc.2019.8832351 ◽

2019 ◽

Author(s):

Shun Sun ◽

Kai Dong ◽

Jun Liu ◽

Chen Guo

Keyword(s):

Vector Field ◽

Target Tracking ◽

Lyapunov Vector ◽

Vector Field Guidance

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Dynamic Path Planning of Flying Projector Considering Collision Avoidance with Observer and Bright Projection

Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion - IUI 18 ◽

10.1145/3180308.3180371 ◽

2018 ◽

Author(s):

Takumi Kawahara ◽

Daisuke Iwai ◽

Kosuke Sato

Keyword(s):

Path Planning ◽

Collision Avoidance ◽

Dynamic Path Planning ◽

Dynamic Path

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Over-flight and standoff tracking of a ground target with a fixed-wing unmanned aerial vehicle based on a unified sliding mode guidance law

Transactions of the Institute of Measurement and Control ◽

10.1177/01423312211037618 ◽

2021 ◽

pp. 014233122110376

Author(s):

Chuanjian Lin ◽

Jingping Shi ◽

Yongxi Lyu ◽

Yueping Wang

Keyword(s):

Target Tracking ◽

Sliding Mode ◽

Practical Application ◽

Stationary Target ◽

Guidance Law ◽

Ground Target ◽

Aerial Vehicle ◽

Standoff Tracking ◽

The Stability ◽

Guidance Laws

Target tracking of ground targets is a significant application of unmanned aerial vehicles (UAVs) in civil and military fields. There are two common modes for target tracking: over-flight tracking and standoff tracking. Each tracking method has a wide application prospect. However, many researchers have studied these two tracking methods separately and designed different guidance laws, which is not conducive to practical application. In this paper, a new guidance law based on sliding mode guidance (SMG) is proposed for tracking a stationary target, which is compatible with the two tracking modes. The stability and finite-time convergence of the guidance law are proved. Then, the guidance is extended to tracking a moving target. The numerical simulations are carried out for the tracking problems of ground targets, and the results verify the effectiveness of the proposed guidance law.

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