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四旋翼无人机具有机动敏捷、操作灵活的优点，能够在特殊环境下代替人类 完成特定任务。在许多实际任务中，四旋翼无人机需要在无全球导航卫星系统 （GNSS）的复杂环境中跟踪地面上的运动目标，四旋翼无人机自主目标跟踪是四 旋翼无人机研究的重要方向之一。本文针对四旋翼无人机在无 GNSS 环境下自 主跟踪地面运动目标展开研究，主要研究内容概要如下：

1. 实现了一种基于非线性优化的视觉惯性里程计，该里程计融合相机和 IMU 等机载传感器信息进行无人机的状态估计。基于相机和 IMU 获得的观测信息，该视觉惯性里程计利用特征点重投影误差和预积分误差来分别构造相机残 差和 IMU 残差，通过联合最小化相机残差和 IMU 残差计算估计状态，其优化目标是非线性最小二乘问题。为降低计算复杂度，优化变量被限制在固定长度的滑动窗口上，并通过边缘化滑动该窗口，以保持视觉惯性里程计的实时性。

2. 实现了一种基于贝塞尔曲线的轨迹规划方法，为无人机生成安全、光滑和动力学可行的轨迹。本文将无人机在三维空间中的轨迹表示为分段贝塞尔曲线，并以最小控制输入为目标函数生成最优轨迹。贝塞尔曲线的性质决定了无人机的位置及各阶导数能被控制点限制在安全区域和动力学可行区域内，故无人机的运动约束可以表示为线性等式和线性不等式约束。结合最优轨迹的目标函数和线性约束，无人机的轨迹通过求解二次规划问题生成。

3. 提出了一个基于视觉的无人机运动目标跟踪系统，并开展了仿真及实验研究。在该系统中，无人机首先根据视觉惯性里程计估计自身状态，并通过扩展卡尔曼滤波从有噪声的视觉测量中估计目标物体状态，进而将无人机目标跟踪问题转化为基于优化的轨迹规划问题。在跟踪目标的过程中，无人机的期望轨迹既需要减小无人机与地面目标之间的跟踪误差，也需要满足安全、光滑和动力学可行的要求。因此，该轨迹规划的目标函数为三种目标的加权和，即无人机与目标之间的跟踪误差、无人机控制输入和无人机轨迹长度，无人机的运动约束则表示为线性约束。最后，本文开展了目标跟踪仿真和实验研究，进行了实验分析，验证了该系统能够实现基于视觉的无人机运动目标跟踪。

Quadrotors are agile and flexible platforms for both academic research and industrial applications, and are capable of operating tasks in challenging environments for humans. Many of these tasks require quadrotors to track a moving target on the ground in complex environments where GNSS is unavailable. This thesis addresses the issue of autonomously tracking a moving target for a quadrotor in GNSS-denied environments. The main contributions of the thesis are summarized as follows.
1. This thesis implements an optimization-based visual-inertial odometry for state estimation of the quadrotor. Collecting measurements from the camera and the IMU, the camera residual is obtained by the reprojection error of the feature points, and the IMU residual by the preintegration error. The visual-inertial odometry estimates the states of the quadrotor by jointly minimizing the camera residual and the IMU residual and solving a nonlinear least square problem. To maintain a real-time performance of the visual-inertial odometry, the optimization is limited on a sliding window of a fixed size by marginalization.
2. This thesis presents a trajectory generation method based on piecewise Bézier curve, which plans safe, smooth and dynamically feasible motions for quadrotors. The trajectory of the quadrotor in the 3D space is represented as the piecewise Bézier curve using Bernstein polynomial basis, and generated by minimizing the control effort on the trajectory of the quadrotor as the cost function. With the special properties of Bézier curves, the position of the entire trajectory and its derivatives can be bounded within the safe and feasible spaces by the control points. Therefore, the motion constraints of the trajectory are enforced in the form of linear equalities and inequlities. Combining the cost function and the linear constraints of the optimal trajectory, the trajectory of the quadrotor is generated by solving a quadratic programming.
3. This thesis proposes a vision-based moving target tracking system of quadrotors with visual-inertial localization. The visual-inertial odometry is utilized to estimate the states of the UAV by fusing visual and inertial measurements, and the states of the target are estimated by extended Kalman Filter from visual detection. This research formulates the target tracking problem as optimization-based trajectory generation, and a weighted sum cost function jointly penalizes the tracking error, the control cost of the trajectory and the trajectory length, while the safety and feasibility constraints are enforced. Simulations and real-world experiments are conducted to validate the effectiveness of the system.