In recent years, multi-rotor aircraft has become the main form for drones. Compared to the helicopters, multi-rotor aircrafts feature simpler structure and cheaper cost; compared to fixed-wing aircrafts, multi-rotor aircrafts are easier to operate and ready to hover with less requirements for the flying fields. This helps explain why a wide range of drones from aircraft toys to industrial drones are made into multi-rotor ones.
All multi-rotor aircrafts are similar in mechanical structure where you only have to mount the propellers on the motor, yet their flight performance varies due to different flight controllers. The flight controller can ensure precise operation and stable hovering by controlling the motor speed, making it possible for beginners to quickly get the hang of drones through simple learning. So to speak, a drone’s performance is mainly decided by its flight controller.
Before attitude control and navigation, the flight controller needs to check the aircraft’s flight status first, which includes 15 parameters such as the three-dimensional location, three-dimensional speed, three-dimensional acceleration, three-axis angle and angular speed. As the multi-rotor aircraft itself is not stable, the motor power has to be constantly tuned for stable hovering and flying. Therefore, even for the simplest action of releasing the joysticks to keep the aircraft hovering, the flight controller has to consistently monitor the 15 parameters and conduct a series of “cascade control” in order to achieve stable hovering.
The first technical difficulty for the flight controller is to precisely perceive the flight status. At present, drones normally use GPS, IMU, barometer and magnetic compass to measure these parameters. The GPS can track the location, sometimes even the altitude and speed; IMU can measure the drone’s three-axis acceleration and three-axis angular speed, and obtain the speed and location through calculation; the barometer is used to measure the height above sea level; the magnetic compass is used for orientation and navigation.
Due to limited sensor design level at present, the data collected by these sensors will generate certain errors and might be disturbed by the environment, consequently reducing the precision of flight status. In order to guarantee normal flight performance, the data collected from different sensors should be fully integrated to conclude 15 high-credibility parameters. We call it as integrated navigation technology which makes the most of the advantages of the GPS, IMU, barometer and magnetic compass and integrates various sensors’ values through electronic signal processing technologies to acquire more precise status measurement.
In order to improve the drones’ sensory ability and flight performance, apart from adopting basic sensors mentioned above, DJI also equips its popular drones with advanced vision sensors, ultrasonic sensors, and redundant IMU and Compass navigation system. For example, DJI Inspire 2, Phantom 4 series and Mavic Pro are equipped with these sensors and intelligent navigation solutions. The dual vision sensors can calculate the object’s three-dimensional location based on continuous images. In addition to obstacle avoidance, it also supports positioning and speed measurement. The ultrasonic sensor can help monitor the flight height. Thanks to the redundant IMU and Compass, when the system detects an inconsistency in one sensor, it switches to the other one, keeping your flight steady and reliable.
The intelligent navigation system in addition to these sensors can increase the drone’s accessibility to more environments and improve its reliability. The drones using traditional navigation system cannot fly stably in environment without GPS while the intelligent navigation system can improve the precision of speed and location measurement through visual sensing system with good GPS signal. With weak GPS signal, the visual sensing system can replace the GPS to provide positioning and speed measurement so that the drone can fly stably indoors and outdoors.
These sensors have significantly improved the intelligent navigation system’s data volume and complexity. Regarding the vision and sensors, DJI conducts several system reconfigurations for the navigation and flight control algorithm and adds new software modules and architectures, comprehensively improving the flight performance and reliability.
Advanced control algorithm empowers DJI’s flight controller with remarkable control quality, featuring high control precision at normal flight state and ensuring stable and high-speed flight. The Inspire 2 can reach a maximum horizontal speed of 94 km/h, the Phantom 4 can reach 72km/h and the compact Mavic can reach 65 km/h, while other similar drones can only reach 30 to 50 km/h. High-speed flight requires high control quality and response speed in addition to powerful propulsion system. Apart from high-speed flight, DJI drones also support high-precision hovering and idling control, making for flexible flying and image composition.
While designing the flight controller, DJI not only pays attention to the control precision at normal flight state, such as hovering position and attitude control precision, but also particularly enhances the control quality for unusual flight status. In case of broken propellers, sudden clash, added weight or external force interference, DJI drones feature strong recovery ability and robustness and can survive various extreme situations, keeping your flight safe and reliable.
Before or during the flight, any tiny fault may result in flight accidents. If the flight controller can monitor and diagnose faults in real time, the probability of accidents can be dramatically lowered. The flight controller can monitor various flight status parameters such as vibration, voltage, current, temperature and motor speed and diagnose potential fault through these characteristic signals. Yet these signals are generally complex and irregular. Based on massive data mining and Deep Learning technology, DJI builds a fault diagnosis system to tell the fault probability through pattern recognition. The fault diagnosis system enables early forecast or emergency treatment of various faults such as broken propellers or IMU failure, helping you fly without worry.