论文标题
用于安全至关重要的航空机器人的避免障碍驱动的控制器
Obstacle avoidance-driven controller for safety-critical aerial robots
论文作者
论文摘要
本论文的目的是提出控制控制器功能（CBF）与模型预测性控制（MPC）的组合，从而导致新型的模型预测性控制性控制 - 控制型伴侣功能（MPCBF）。可以证明，由于MPC的时间范围增加，MPCBF的性能超过了CBF的性能。此外，将MPCBF应用于四个四方，这是一个非常需要快速和预测性控制的系统。使用MPCBF，四摩托器能够避免障碍，因为障碍物的相对速度，CBF无法避免这种障碍。这项工作的结果经过实验验证。
The goal of this thesis is to propose the combination of Control-Barrier-Functions (CBF) with Model-Predictive-Control (MPC) resulting in the novel Model-Predictive-Control-Barrier-Function (MPCBF). It can be shown, that the performance of the MPCBF surpasses the performance of the CBF due to the increased time horizon of the MPC. Moreover, the MPCBF was applied to a quadrotor, a system strongly in need of fast and predictive control. Using the MPCBF, the quadrotor was able to avoid obstacles, which the CBF failed to avoid due to the relative speed of the obstacle. The results of this work are experimentally validated.
