  This paper studies quadcopters obstacle avoidance trajectory control (OATC)
problem for express delivery. A new nonlinear adaptive learning controller that
is low-cost and portable to different wheelbase sizes is proposed to adapt to
large-angle maneuvers and load changes in UAV delivery missions. The controller
consists of a nonlinear variable gain (NLVG) function and an extreme value
search (ES) algorithm to reduce overshoot and settling time. Finally,
simulations were conducted on a quadcopter to verify the effectiveness of the
proposed control scheme under two typical collision-free trajectories.
