TY - JOUR
T1 - UAV Swarm Control Based on Hybrid Bionic Swarm Intelligence
AU - Fan, Ruitao
AU - Wang, Jintao
AU - Han, Weixin
AU - Xu, Bin
N1 - Publisher Copyright:
#c Technical Committee on Guidance, Navigation and Control, CSAA and World Scienti¯c Publishing Co.
PY - 2023/6/1
Y1 - 2023/6/1
N2 - Inspired by the pigeon behavior pattern, this paper proposes an Unmanned Aerial Vehicle (UAV) swarm control scheme based on hybrid bionic swarm intelligence, which can realize multi-UAV obstacle avoidance during formation control. First, the leadership mechanism of pigeon °ock is mapped to UAV swarm, and the virtual leaders are introduced to solve the un¯xed relative position of level-1 leader problem. Second, the control law for UAV swarm formation is designed based on arti¯cial potential ¯eld theory and analysis of the bionic mechanism. To avoid local minima, a guidance phase is added to the UAV formation process. By analyzing the °ocking algorithm, a cooperative interaction control model of UAV swarm is established. Third, the cooperative interactive control law for UAV swarm obstacle avoidance is proposed based on improved arti¯cial potential ¯eld function. Then the two bionic swarm control models are combined to realize the formation and obstacle avoidance of UAV swarm based on mixed bionic swarm intelligence. Finally, a series of simulations are conducted to demonstrate the proposed hybrid UAV swarm control algorithm.
AB - Inspired by the pigeon behavior pattern, this paper proposes an Unmanned Aerial Vehicle (UAV) swarm control scheme based on hybrid bionic swarm intelligence, which can realize multi-UAV obstacle avoidance during formation control. First, the leadership mechanism of pigeon °ock is mapped to UAV swarm, and the virtual leaders are introduced to solve the un¯xed relative position of level-1 leader problem. Second, the control law for UAV swarm formation is designed based on arti¯cial potential ¯eld theory and analysis of the bionic mechanism. To avoid local minima, a guidance phase is added to the UAV formation process. By analyzing the °ocking algorithm, a cooperative interaction control model of UAV swarm is established. Third, the cooperative interactive control law for UAV swarm obstacle avoidance is proposed based on improved arti¯cial potential ¯eld function. Then the two bionic swarm control models are combined to realize the formation and obstacle avoidance of UAV swarm based on mixed bionic swarm intelligence. Finally, a series of simulations are conducted to demonstrate the proposed hybrid UAV swarm control algorithm.
KW - UAV
KW - arti¯cial potential ¯eld
KW - formation control
KW - obstacle avoidance
KW - pigeon °ock leadership mechanism
KW - °ocking algorithm
UR - https://www.scopus.com/pages/publications/85168750223
U2 - 10.1142/S2737480723500085
DO - 10.1142/S2737480723500085
M3 - 文章
AN - SCOPUS:85168750223
SN - 2737-4807
VL - 3
JO - Guidance, Navigation and Control
JF - Guidance, Navigation and Control
IS - 2
M1 - 2350008
ER -