Proceedings Article10.23919/CHICC.2017.8028347
UAV formation control with obstacle avoidance using improved artificial potential fields
Yuanchen Zhao,Lu Jiao,Rui Zhou,Jie Zhang +3 more
- 01 Jul 2017
- pp 6219-6224
52
TL;DR: An improved artificial potential field (APF) method is proposed for solving the problem of UAV formation control with obstacle avoidance in a complex environment and simulation results demonstrate the effectiveness of the improved APF method.
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Abstract: Researches on unmanned aerial vehicle (UAV) formation control are attracting more and more researchers' attention. Obstacle avoidance is a key problem of UAV formation. In this paper, an improved artificial potential field (APF) method is proposed for solving the problem of UAV formation control with obstacle avoidance in a complex environment. Point-mass models with kinematic constraints have been employed for UAVs, and autopilots are modelled as first-order systems. Structural constraints of desired formation configuration are considered in the design of the attraction potential field among UAVs, which ensures the convergence of UAVs to a given formation configuration for any initial condition. Furthermore, for UAVs flying at high speeds, an improved APF method combined with formation division method is introduced to realize more flexible formation obstacle avoidance in congested settings where many static and dynamic obstacles exist. Finally, simulations of UAV formation keeping and obstacle avoidance are presented. The proposed methods enable UAVs with different initial states to build expected formation, track the desired trajectory and avoid collisions and obstacles during formation flight. The simulation results demonstrate the effectiveness of the improved APF method.
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Citations
Formation Control Algorithms for Multiple-UAVs: A Comprehensive Survey
Hai T. Do,Hoang T. Hua,Minh Tuan Nguyen,Cuong Nguyen,Hoa Tt. Nguyen,Hoa Nguyen,Nga T. T. Nguyen +6 more
- 10 Jun 2021
TL;DR: In this article, the authors present a survey of the formation control in multiple-UAVs systems, highlighting the distinct merits and demerits of different control protocols and their open challenges and research directions.
3D path planning and real-time collision resolution of multirotor drone operations in complex urban low-altitude airspace
TL;DR: A fusion scheme to achieve autonomous drone collision-free path planning considering static obstacles and dynamic threats detected based on the Markov decision process to implement real-time dynamic collision avoidance of multirotor drones.
43
UAV Formation Obstacle Avoidance Control Algorithm Based on Improved Artificial Potential Field and Consensus
Ning Wang,Jiyang Dai,Jin Ying +2 more
TL;DR: A novel distributed obstacle avoidance control algorithm for cooperative formation based on the improved artificial potential field (IAPF) and consensus theory is proposed and can not only prevent the UAV from colliding with each other while avoiding static and dynamic obstacles but also enable theUAV to quickly restore the expected formation and achieve the consensus of the relative distance, relative height, and velocity.
Joint Formation Control with Obstacle Avoidance of Towfish and Multiple Autonomous Underwater Vehicles Based on Graph Theory and the Null-Space-Based Method
Shi-kun Pang,Ying-hui Li,Hong Yi +2 more
TL;DR: Simulation results demonstrate the effectiveness and feasibility of the proposed method in a complex underwater environment with obstacles and the comprehensive output function of formation motion is deduced and established to ensure that obstacles can be avoided effectively.
Piecewise-potential-field-based path planning method for fixed-wing UAV formation
TL;DR: In this paper , a fixed-wing UAV formation path planning method based on piecewise potential field (PPF) is proposed, where the problem of formation flight path planning in different states can be solved by suitable design of the PPF function.
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