四旋翼无人机视觉导航与轨迹跟踪

Abstract

With the continuous development of computer hardware technology and software algorithms, the role of quadrotor UA Vs in civil and military applications is increasingly important. Traditional navigation methods and conventional control algorithms have been unable to meet the increasingly complex requirements of quadrotor’s mission. Therefore, this paper will study the quadrotor UA V vision navigation algorithm and trajectory tracking control algorithm.

The flight mechanism of quadrotor UA V is analyzed in this paper and the coordinate system is defined. The coordinate transformation equations based on Euler angles and quaternions are derived and the quadrotor’s kinematics and dynamics model are established. Aiming at the problem that the calculation of desired attitude computed from the position loop based on the Euler angle model is expected to be complex and prone to saturation, a new method is proposed, which can obtain the desired quaternion from the acceleration obtained by the position loop through geometric transformation and simplify the quadrotor system model. The system model equation establishes the model foundation for the design of the trajectory tracking control system of the quadrotor UA V. The UA V vision navigation system is designed and the function of each part of the system is introduced at the same time.

Aiming at the problem that the GPS navigation methods can not be accurately located when the satellite signal is weak, a target detection algorithm based on L-K optical flow method is designed to realize the detection of dynamic targets. At the same time, this paper studies the target tracking algorithm. The principle of Meanshift algorithm is introduced, and the Camshift target tracking algorithm is implemented based on this. For the problem that the target tracking is easily lost based on the traditional Camshift algorithm in the compliex environment background, the Camshift algorithm fusing the Kalman filter is proposed, which voids the problem of tracking failure when the target is occluded temporarily, and improves the robustness of target tracking system.

Aiming at the problem that the conventional control algorithm can not meet the robustness of the nonlinear model control of the quadrotor UA V, this paper makes a deep study on the active disturbance rejection control(ADRC) algorithm. Firstly, the composition and function of each part of the ADRC are analyzed, and the stability of the ESO is proved. Then, the attitude decoupling controller based on ADRC is proposed to realize the robust control of the attitude loop of the quadrotor UA V; Aiming at the characteristics of the underactuated and multi-channel coupling of the actual quadrotor UA V model, the double closed-loop PID controller of position loop and linaer active disturbance rejection controller of attitude loop based on the quaternion nonlinear model equation are designed, the trajectory tracking control system realizes interference

rejection and track the reference signals accurately, which improves the robustness of the system and the simulation shows the effective compared with the PID .

Finally, this paper establishes the hardware platform and software platform of quadrotor UA V vision navigation and trajectory tracking system, and some tests are carried out based the actual system. The quadrotor UA V trajectory tracking test is completed base on the open-source Pixhawk flight control system; hovering indoors and target tracking of quadrotor UA V are tested base on the designed vision navigation algorithms.

Keywords: Quadrotor UA V, vision navigation，L-K Optical flow, Camshift, Kalman, ADRC , Trajectory Tracking

摘要 ............................................................................................................................... I Abstract............................................................................................................................. I I 第1章绪论 .. (1)

1.1 课题研究的背景和意义 (1)

1.2 国内外研究现状及分析 (3)

1.2.1 视觉检测与跟踪技术 (3)

1.2.2 四旋翼无人机控制方法 (5)

1.3 主要研究内容与结构安排 (6)

1.3.1 本文的研究内容 (6)

1.3.2 本文的组织结构 (7)

第2章四旋翼无人机数学建模 (9)

2.1 引言 (9)

2.2 四旋翼无人机工作原理分析 (9)

2.3 四旋翼无人机的动力学模型建立及分析 (10)

2.3.1 坐标系定义及姿态描述 (10)

2.3.2 四旋翼无人机动力学模型 (11)

2.4 视觉导航系统设计 (16)

2.5 本章小结 (18)

第3章视觉导航算法设计 (19)

3.1 引言 (19)

3.2 基于L-K光流法的运动检测 (19)

3.3 Camshift目标跟踪算法 (22)

3.3.1 Meanshift算法原理 (22)

3.3.2 Camshift算法原理 (26)

3.3.3 融合Kalman滤波的Camshift算法实现 (29)

3.3.4 实验结果 (32)

3.4 本章小结 (34)

第4章四旋翼无人机轨迹跟踪控制系统设计 (35)

4.1 引言 (35)

4.2 自抗扰控制器原理 (35)

4.3 基于自抗扰的四旋翼姿态解耦控制器设计 (42)

4.3.1 姿态自抗扰控制器设计 (42)

4.3.2 数值仿真分析 (43)

4.4 基于非线性模型的控制器设计 (47)

4.4.1 位置环PD控制器设计 (47)

4.4.2 姿态环线性自抗扰控制器设计 (48)

4.4.3 数值仿真分析 (50)

4.5 本章小结 (53)

第5章系统平台搭建与飞行实验 (54)

5.1 引言 (54)

5.2 系统平台设计 (54)

5.2.1 硬件平台 (54)

5.2.2 软件架构 (56)

5.3 四旋翼无人机实际飞行测试 (57)

5.3.1 轨迹跟踪实验 (57)

5.3.2 光流悬停实验 (59)

5.3.3 目标跟踪实验 (62)

5.4 本章小结 (65)

结论 (66)

参考文献 (68)

攻读硕士学位期间发表的论文及其它成果 (73)

哈尔滨工业大学学位论文原创性声明和使用权限 (74)

致谢 (75)