  This paper proposes a perception-shared and swarm trajectory global optimal
(STGO) algorithm fused UAVs formation motion planning framework aided by an
active sensing system. First, the point cloud received by each UAV is fit by
the gaussian mixture model (GMM) and transmitted in the swarm. Resampling from
the received GMM contributes to a global map, which is used as the foundation
for consensus. Second, to improve flight safety, an active sensing system is
designed to plan the observation angle of each UAV considering the unknown
field, overlap of the field of view (FOV), velocity direction and smoothness of
yaw rotation, and this planning problem is solved by the distributed particle
swarm optimization (DPSO) algorithm. Last, for the formation motion planning,
to ensure obstacle avoidance, the formation structure is allowed for affine
transformation and is treated as the soft constraint on the control points of
the B-spline. Besides, the STGO is introduced to avoid local minima. The
combination of GMM communication and STGO guarantees a safe and strict
consensus between UAVs. Tests on different formations in the simulation show
that our algorithm can contribute to a strict consensus and has a success rate
of at least 80% for obstacle avoidance in a dense environment. Besides, the
active sensing system can increase the success rate of obstacle avoidance from
50% to 100% in some scenarios.
