A Review of quadrotor UAV: Control and SLAM methodologies ranging from conventional to innovative approaches

Sonugür, Güray

doi:10.1016/j.robot.2022.104342

Cited by 34 publications

(16 citation statements)

References 130 publications

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“…and inversely solve for the desired trajectory by (9) corresponding to the desired attitude angle dd  、 : arcsin( / sin sin ) / (cos cos ))…”

Section: B Outer Ring Position Trackingmentioning

confidence: 99%

Disturbance feedforward compensation based on Modelica modeling with the Self-immunity study of a quadrotor UAV

ZHOU,

BAO,

LIANG

et al. 2023

Preprint

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Due to the nonlinearity, underactuated, strong coupling, multi-data flow direction, and vulnerability to internal and external disturbances, the widely used PID control technology has been very difficult. Some emerging nonlinear control theory algorithms have good simulation performance, but they rely heavily on exact mathematical models, require a large amount of computation, and take a long time to solve. Therefore, based on the advantages of non-causal declarative modeling in Modelica language, this paper focuses on the analysis and implementation of the mechanism of observation, estimation, and compensation of nonlinear ADRC disturbances, PID-NLADRC linear nonlinear combined control strategy is designed to realize the flight control of a four-rotor UAV. The multi-target applications, such as fixed-point hover, cone spiral trajectory tracking and air obstacle avoidance fillet moment trajectory tracking, are verified respectively. The simulation results show that the designed PID-NLADRC control strategy has better performance than the Cascade PID control strategy in suppressing the fixed-point hover disturbance, it is fully verified that the PID-NLADRC control strategy has a smaller Euclidean range deviation and stronger disturbance rejection ability for tracking trajectories with different properties such as plane or space, smooth or transient, it can better meet the requirements of fast, accurate and robust flight control of four-rotor UAV.

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“…and inversely solve for the desired trajectory by (9) corresponding to the desired attitude angle dd  、 : arcsin( / sin sin ) / (cos cos ))…”

Section: B Outer Ring Position Trackingmentioning

confidence: 99%

Disturbance feedforward compensation based on Modelica modeling with the Self-immunity study of a quadrotor UAV

ZHOU,

BAO,

LIANG

et al. 2023

Preprint

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show abstract

“…An effective method is simultaneous localization and mapping (SLAM) technology. Thanks to its mature application on ground robots, SLAM has been gradually transplanted to the field of navigation and obstacle avoidance on UAVs and has achieved good results [8][9][10]. SLAM establishes a 3D environment map based on the flight scene information obtained by the sensor to guide the flight of UAV, but it relies on intricate scene reconstruction algorithms.…”

Section: Introductionmentioning

confidence: 99%

A framework for improving UAV decision of autonomous navigation from training to application migration under perceptual uncertainty

Sheng,

Liu,

et al. 2024

Meas. Sci. Technol.

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Unmanned Aerial Vehicles (UAVs) autonomous navigation based on reinforcement learning (RL) usually requires training agents in simulation scenarios and then transferring the trained agents to application scenarios. However, due to serious distribution mismatch between the idealized simulation scenario and the application environment and the inevitable uncertainty perception problem of airborne sensors in complex scenarios, the navigation performance of UAV under migration applications is not ideal. This work fully analyzes the factors that affect UAV navigation performance, including algorithm performance, training strategy, and state awareness. Based on the analysis results, this article proposes a framework to improve the autonomous navigation performance of UAVs in the migration process from training to application, which consists of three parts: "scenario-perception-algorithm". In addition, this paper proposes improvement strategies for each part from the perspectives of spatial features, temporal features, and perceptual denoising. We combine the proposed framework with navigation algorithms to improve the navigation decision-making performance of UAVs in migration applications under uncertainty perception. Many simulation experiments demonstrate the effectiveness of the proposed framework and its robustness to uncertainty perception.

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“…With the purpose of taking the maximum benefit of the capabilities of these vehicles for tracking purposes, numerous controllers have been proposed [4][5][6]. In [7], successful implementation of linear control techniques, including the linear quadratic regulator (LQR), was achieved for low-speed indoor flights.…”

Section: Introductionmentioning

confidence: 99%

Saturated Trajectory Tracking Controller in the Body-Frame for Quadrotors

Madeiras,

Cardeira,

Oliveira

et al. 2024

Drones

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This paper introduces a quadrotor trajectory tracking controller comprising a steady-state optimal position controller with a normed input saturation and modular integrative action coupled with a backstepping attitude controller. First, the translational and rotational dynamical models are designed in the body-fixed frame to avoid external rotations and are partitioned into an underactuated position system and a quaternion-based attitude system. Secondly, a controller is designed separately for each subsystem, namely, (i) the position controller synthesis is derived from the Maximum Principle, Lyapunov, and linear quadratic regulator (LQR) theory, ensuring the global exponential stability and steady-state optimality of the controller within the linear region, and global asymptotic stability is guaranteed for the saturation region when coupled with any local exponential stable attitude controller, and (ii) the attitude system, with the quaternion angles and the angular velocity as the controlled variables, is designed in the error space through the backstepping technique, which renders the overall system, position, and attitude, with desirable closed-loop properties that are almost global. The overall stability of the system is achieved through the propagation of the position interconnection term to the attitude system. To enhance the robustness of the tracking system, integrative action is devised for both position and attitude, with emphasis on the modular approach for the integrative action on the position controller. The proposed method is experimentally validated on board an off-the-shelf quadrotor to assess the resulting performance.

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A Review of quadrotor UAV: Control and SLAM methodologies ranging from conventional to innovative approaches

Cited by 34 publications

References 130 publications

Disturbance feedforward compensation based on Modelica modeling with the Self-immunity study of a quadrotor UAV

Disturbance feedforward compensation based on Modelica modeling with the Self-immunity study of a quadrotor UAV

A framework for improving UAV decision of autonomous navigation from training to application migration under perceptual uncertainty

Saturated Trajectory Tracking Controller in the Body-Frame for Quadrotors

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