Quadrocopter Hovering Using Position-estimation Information from Inertial Sensors and a High-delay Video System
The requirement that mobile robots become independent of external sensors, such as GPS, and are able to navigate in an environment by themselves, means that designers have few alternative techniques available. An increasingly popular approach is to use computer vision as a source of information about the surroundings. This paper presents an implementation of computer vision to hold a quadrocopter aircraft in a stable hovering position using a low-cost, consumer-grade, video system. However, such a system is not able to stabilize the aircraft on its own and must rely on a data-fusion algorithm that uses additional measurements from on-board inertial sensors. Special techniques had to be implemented to compensate for the increased delay in the closed-loop system with the computer vision system, i.e., video timestamping to determine the exact delay of the vision system and a slight modification of the Kalman filter to account for this delay. At the end, the validation results of the proposed filtering technique are presented along with the results of an autonomous flight as a proof of the proposed concept.
quadrocopter computer vision unmanned aerial vehicle (uav) position estimation delayed measurements low-cost