Formation Control of UGVs Based on Artificial Potential Field

Author(s):  
Lv Yongshen ◽  
Yang Xuerong ◽  
Yang Yajun ◽  
Pan Shengdong
2021 ◽  
Vol 9 (2) ◽  
pp. 161
Author(s):  
Xun Yan ◽  
Dapeng Jiang ◽  
Runlong Miao ◽  
Yulong Li

This paper proposes a formation generation algorithm and formation obstacle avoidance strategy for multiple unmanned surface vehicles (USVs). The proposed formation generation algorithm implements an approach combining a virtual structure and artificial potential field (VSAPF), which provides a high accuracy of formation shape keeping and flexibility of formation shape change. To solve the obstacle avoidance problem of the multi-USV system, an improved dynamic window approach is applied to the formation reference point, which considers the movement ability of the USV. By applying this method, the USV formation can avoid obstacles while maintaining its shape. The combination of the virtual structure and artificial potential field has the advantage of less calculations, so that it can ensure the real-time performance of the algorithm and convenience for deployment on an actual USV. Various simulation results for a group of USVs are provided to demonstrate the effectiveness of the proposed algorithms.


2020 ◽  
Vol 124 (1282) ◽  
pp. 1979-2000
Author(s):  
A. Mirzaee Kahagh ◽  
F. Pazooki ◽  
S. Etemadi Haghighi

ABSTRACTA formation control and obstacle avoidance algorithm has been introduced in this paper for the V-shape formation flight of fixed-wing UAVs (Unmanned Aerial Vehicles) using the potential functions method. An innovative vector approach has been suggested to fix the conventional challenge in employing the artificial potential field (APF) approach (the creation of local minimums). A method called variable repulsive circles (VRC) has been then presented aimed at designing proper flight paths tailored with functional limitations of fixed-wing UAVs in facing obstacles. Finally, the efficiency of the designed algorithm has been examined and evaluated for different flight scenarios.


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