Thrust Mixing, Saturation, and Body-Rate Control for Accurate Aggressive Quadrotor Flight

By Matthias Faessler, Davide Falanga, Davide Scaramuzza. 2017

137 citations recorded by the source corpus.

Quadrotors are well suited for executing fast maneuvers with high accelerations but they are still unable to follow a fast trajectory with centimeter accuracy without iteratively learning it beforehand. In this paper, we present a novel body-rate controller and an iterative thrust-mixing scheme, which improve the trajectory-tracking performance without requiring learning and reduce the yaw control error of a quadrotor, respectively. Furthermore, to the best of our knowledge, we present the first algorithm to cope with motor saturations smartly by prioritizing control inputs which are relevant for stabilization and trajectory tracking. The presented body-rate controller uses LQR-control methods to consider both the body rate and the single motor dynamics, which reduces the overall trajectory-tracking error while still rejecting external disturbances well. Our iterative thrust-mixing scheme computes the four rotor thrusts given the inputs from a position-control pipeline. Through the iterative computation, we are able to consider a varying ratio of thrust and drag torque of a single propeller over its input range, which allows applying the desired yaw torque more precisely and hence reduces the yaw-control error. Our prioritizing motor-saturation scheme improves stability and robustness of a quadrotor's flight and may prevent unstable behavior in case of motor saturations. We demonstrate the improved trajectory tracking, yaw-control, and robustness in case of motor saturations in real-world experiments with a quadrotor.

Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering, Ocean Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Jeffrey A. Delmerico
2. Davide Scaramuzza
3. Davide Falanga
4. Alessandro Simovic
5. Alessio Zanchettin
6. Vladlen Koltun
7. Daniel Cremers
8. Guoquan Huang

In Control and Systems Engineering

1. Davide Scaramuzza
2. Jeffrey A. Delmerico
3. Alessandro Simovic
4. Alessio Zanchettin
5. Davide Falanga

In Ocean Engineering

1. Davide Scaramuzza

Citations in the corpus

• Vision-based autonomous quadrotor landing on a moving platform (2017, methodology): “We refer the reader to our previous works [27] and [28] for further details on the dynamical model and the control algorithm used in this work.”