A Vision-based Autonomous Perching Approach for Nano Aerial Vehicles
Truong-Dong Do Sung Kyung Hong
Over the past decades, quadcopters have been investigated, due to their
mobility and flexibility to operate in a wide range of environments. They have
been used in various areas, including surveillance and monitoring. During a
mission, drones do not have to remain active once they have reached a target
location. To conserve energy and maintain a static position, it is possible to
perch and stop the motors in such situations. The problem of achieving a
reliable and highly accurate perching method remains a challenge and promising.
In this paper, a vision-based autonomous perching approach for nano quadcopters
onto a predefined perching target on horizontal surfaces is proposed. First, a
perching target with a small marker inside a larger one is designed to improve
detection capability at a variety of ranges. Second, a monocular camera is used
to calculate the relative poses of the flying vehicle from the markers
detected. Then, a Kalman filter is applied to determine the pose more reliably,
especially when measurement data is missing. Next, we introduce an algorithm
for merging the pose data from multiple markers. Finally, the poses are sent to
the perching planner to conduct the real flight test to align the drone with
the target's center and steer it there. Based on the experimental results, the
approach proved to be effective and feasible. The drone can successfully perch
on the center of markers within two centimeters of precision.