Cooperative UAVs Formation Reconfiguration in an Obstacle-Loaded Environment via Model Predictive Control
Hafez, A., Givigi, S. (2015). Cooperative UAVs Formation Reconfiguration in an Obstacle-Loaded Environment via Model Predictive Control. EKB Journal Management System, 16(AEROSPACE SCIENCES & AVIATION TECHNOLOGY, ASAT - 16 – May 26 - 28, 2015), 1-19. doi: 10.21608/asat.2015.23004
Ahmed Taimour Hafez; Sidney N. Givigi. "Cooperative UAVs Formation Reconfiguration in an Obstacle-Loaded Environment via Model Predictive Control". EKB Journal Management System, 16, AEROSPACE SCIENCES & AVIATION TECHNOLOGY, ASAT - 16 – May 26 - 28, 2015, 2015, 1-19. doi: 10.21608/asat.2015.23004
Hafez, A., Givigi, S. (2015). 'Cooperative UAVs Formation Reconfiguration in an Obstacle-Loaded Environment via Model Predictive Control', EKB Journal Management System, 16(AEROSPACE SCIENCES & AVIATION TECHNOLOGY, ASAT - 16 – May 26 - 28, 2015), pp. 1-19. doi: 10.21608/asat.2015.23004
Hafez, A., Givigi, S. Cooperative UAVs Formation Reconfiguration in an Obstacle-Loaded Environment via Model Predictive Control. EKB Journal Management System, 2015; 16(AEROSPACE SCIENCES & AVIATION TECHNOLOGY, ASAT - 16 – May 26 - 28, 2015): 1-19. doi: 10.21608/asat.2015.23004

Cooperative UAVs Formation Reconfiguration in an Obstacle-Loaded Environment via Model Predictive Control

International Conference on Aerospace Sciences and Aviation Technology
Article 65, Volume 16, AEROSPACE SCIENCES & AVIATION TECHNOLOGY, ASAT - 16 – May 26 - 28, 2015, May 2015, Page 1-19  XML PDF (661.79 K)
Document Type: Original Article
DOI: 10.21608/asat.2015.23004
View on SCiNiTO View on SCiNiTO
Authors
Ahmed Taimour Hafez1; Sidney N. Givigi2
1Egyptian Armed Forces, Egypt.
2Associate Professor in the ECE Department, Royal Military Collage (RMC), Canada.
Abstract
Recently, Unmanned Aerial Vehicles (UAVs) have attracted a great deal of attention in academic, civilian and military communities as prospective solutions to a wide variety of applications. The use of cooperative UAVs has received growing interest in the last decade and this provides an opportunity for new operational paradigms. In this paper, the problem of formation reconfiguration for a group of N cooperative UAVs in an obstacle-loaded environment is solved using decentralized Learning Based Model Predictive Control (LBMPC). The formation of the multiple cooperative UAVs respects the general rules of flocking known as Reynold’s rules. Each UAV is required to avoid collision with nearby flockmates, attempts to match the velocity of other team members and attempts to stay close to other team members respecting the desired formation. When static obstacles appear, the UAVs are required to steer around the obstacle or pass through avoiding collision with the obstacles or with each other. A state transformation algorithm is applied to linearize the UAV dynamics generating a linear system allowing the implementation in real life. Our main contribution in this paper lays in solving the formation reconfiguration problem for a group of cooperative UAVs forming a desired formation using decentralized LBMPC in the presence of obstacles.
Keywords
Unmanned Aerial Vehicles; Cooperative UAVs; Learning Based Model Predictive Control
Statistics
Article View: 134
PDF Download: 224