Zhu Yixin's research group of the Artificial Intelligence Research Institute has made important progress in enhancing the stability and safety of the drive UAV platform

Recently, the research group of Assistant Professor Zhu Yixin of the Institute of Artificial Intelligence of Peking University published a paper "Downwash-Aware Control Allocation for Overactuated UAV Platforms" at IROS 2022, introducing a control strategy

Overdrive drone platform based on multiple quadcopters and passive degrees of freedom mechanism

Because of its dexterity and simplicity, drones have been attracting the attention of

Down-wash effects (Chinese can be translated as airflow erosion phenomena) during multi-machine collaboration have been a concern for researchers in the field

What is the phenomenon of airflow erosion between drones? We can think of the airflow generated by the quadcopter drone as it flies as a cylindrical airflow field

Much of the existing research on drone Down-wash effects has focused on

The phenomenon of airflow erosion affects the drone flight below

The phenomenon of airflow erosion interferes with the drive drone's flip

Unlike existing research, this study is the first to target Down-wash effects on overdriven drone platforms

An overdrive drone platform consisting of several omnidirectional thrust modules can have an infinite number of control allocation schemes to generate the same wrench command.

Intuitively, if you want the airflow between the various drone modules not to wash over each other, you only need to tilt the modules in different directions and avoid each other

The researchers conducted experiments in both the simulation environment and the actual environment to verify the effectiveness

Traditional methods as well as control allocation are compared on a platform with four omnidirectional thrust modules

Traditional methods as well as control allocation are compared on a platform with six omnidirectional thrust modules

It can be clearly seen that using traditional control algorithms, Down-wash effects will be encountered in some positions, at which point the drone platform will have a noticeable vertical fall

The traditional method, along with control allocation, was experimentally validated on a drone platform with four omnidirectional thrust modules

The actual experimental phenomena are the same as the simulation results, which supports the control algorithm

Control the effect comparison under different adjustment thresholds in Omin cases

It should be noted that the control algorithm proposed in this study can be used for overdriven UAV platforms with any number of quadcopter modules, so it has strong scalability

In this work, the control algorithm proposed by the researchers cleverly balances the Down-wash effects that drive the drone platform and the thrust efficiency

References:

[1] Su, Yao, et al.

[2] Su, Yao, et al.

[3] Yu, Pengkang, et al.

[4] Pi Chen-Huan, et al.
“A Simple Six Degree-of-Freedom Aerial Vehicle Built on Quadcopters”in Proceedings of IEEE Conference on Control Technology Applications (CCTA), 2021

[5] Gerber, Matthew J.
, et al.
“Twisting and Tilting Rotors for High-efficiency, Thrust-vectored Quadrotors,” Journal of Mechanisms and Robotics, vol.
10, no.
6, p.
061013, 2018.