TY - JOUR
T1 - Efficient unmanned aerial vehicle formation rendezvous trajectory planning using Dubins path and sequential convex programming
AU - Wang, Zhu
AU - Liu, Li
AU - Long, Teng
AU - Xu, Guangtong
N1 - Publisher Copyright:
© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2019/8/3
Y1 - 2019/8/3
N2 - Trajectory planning of formation rendezvous of multiple unmanned aerial vehicles (UAVs) is formulated as a mixed-integer optimal control problem, and an efficient hierarchical planning approach based on the Dubins path and sequential convex programming is proposed. The proposed method includes the assignment of rendezvous points (high level) and generation of cooperative trajectories (low level). At the high level, the assignment of rendezvous points to UAVs is optimized to minimize the total length of Dubins-path-based approximate trajectories. The assignment results determine the geometric relations between the UAVs’ goals, which are used as equality constraints for generating trajectories. At the low level, trajectory generation is treated as a non-convex optimal control problem, which is transformed to a non-convex parameter optimization and then solved via sequentially performing convex optimization. Numerical experiments demonstrate that the proposed method can generate feasible trajectories and can outperform a typical nonlinear programming method in terms of efficiency.
AB - Trajectory planning of formation rendezvous of multiple unmanned aerial vehicles (UAVs) is formulated as a mixed-integer optimal control problem, and an efficient hierarchical planning approach based on the Dubins path and sequential convex programming is proposed. The proposed method includes the assignment of rendezvous points (high level) and generation of cooperative trajectories (low level). At the high level, the assignment of rendezvous points to UAVs is optimized to minimize the total length of Dubins-path-based approximate trajectories. The assignment results determine the geometric relations between the UAVs’ goals, which are used as equality constraints for generating trajectories. At the low level, trajectory generation is treated as a non-convex optimal control problem, which is transformed to a non-convex parameter optimization and then solved via sequentially performing convex optimization. Numerical experiments demonstrate that the proposed method can generate feasible trajectories and can outperform a typical nonlinear programming method in terms of efficiency.
KW - Unmanned aerial vehicle
KW - convex optimization
KW - formation rendezvous
KW - trajectory optimization
UR - http://www.scopus.com/inward/record.url?scp=85054781770&partnerID=8YFLogxK
U2 - 10.1080/0305215X.2018.1524461
DO - 10.1080/0305215X.2018.1524461
M3 - Article
AN - SCOPUS:85054781770
SN - 0305-215X
VL - 51
SP - 1412
EP - 1429
JO - Engineering Optimization
JF - Engineering Optimization
IS - 8
ER -