Open AccessAutonomous Navigation and Control System for Capturing A Moving Drone
Author(s) -
Hong Tao,
Tao Song,
Defu Lin,
Jin Ren,
Bin Li
Publication year - 2022
Publication title -
field robotics
Language(s) - English
Resource type - Journals
ISSN - 2771-3989
DOI - 10.55417/fr.2022002
Subject(s) - drone , trajectory , computer science , position (finance) , inertial navigation system , acceleration , artificial intelligence , computer vision , navigation system , air navigation , simulation , inertial frame of reference , global positioning system , telecommunications , physics , genetics , finance , classical mechanics , quantum mechanics , astronomy , economics , biology
This paper describes an autonomous navigation and control system for capturing the maneuvering drones. A vision-based navigation method seeks and detects the intruding drone, then, the target trajectory is predicted by fusing onboard vision and inertial-measurement resources. The target’s relative position, velocity and acceleration are also obtained at the same time. Then, we present a modified proportional-derivative (PD) algorithm based on the estimated target states. In addition, the boundary constraints of the protected area are considered to avoid a collision. The proposed capture navigation and control system has demonstrated its efficiency both in simulation, flight experiments, and MBZIRC 2020, where our team won the Challenge I competition.