  The paper proposes a novel concept of docking drones to make this process as
safe and fast as possible. The idea behind the project is that a robot with a
soft gripper grasps the drone in midair. The human operator navigates the
robotic arm with the ML-based gesture recognition interface. The 3-finger robot
hand with soft fingers is equipped with touch sensors, making it possible to
achieve safe drone catching and avoid inadvertent damage to the drone's
propellers and motors. Additionally, the soft hand is featured with a unique
color-based force estimation technology based on a computer vision (CV) system.
Moreover, the visual color-changing system makes it easier for the human
operator to interpret the applied forces.
  Without any additional programming, the operator has full real-time control
of the robot's motion and task execution by wearing a mocap glove with gesture
recognition, which was developed and applied for the high-level control of
DroneTrap. The experimental results revealed that the developed color-based
force estimation can be applied for rigid object capturing with high precision
(95.3\%). The proposed technology can potentially revolutionize the landing and
deployment of drones for parcel delivery on uneven ground, structure
maintenance and inspection, risque operations, and etc.
