We present a new integrated guidance and control method for autonomous collision avoidance and navigation in an unmapped GPS-denied environment that contains unknown obstacles. The algorithm is implemented on an experimental custom quadrotor that uses onboard vision sensing (i.e., an Intel RealSense R200) to detect the positions of obstacles. We demonstrate autonomous collision avoidance and destination seeking in experiments, where the quadrotor navigates unknown GPS-denied environments. All feedback measurements are obtained from onboard sensors. The new guidance and control algorithm uses a nonlinear inner-loop attitude controller; a nonlinear middle-loop velocity controller; and an ellipsoidal-potential-field outer-loop guidance algorithm for collision avoidance and destination seeking. The main analytic result regarding the inner-loop control shows that every quadrotor attitude with pitch between \(\pm 90^{\circ }\) is a locally exponentially stable equilibrium of the closed-loop attitude dynamics, and we quantify the region of attraction for each attitude equilibrium.

我们提出了一种新的集成制导和控制方法，用于在未映射的GPS拒绝的环境中（包含未知障碍）进行自动避碰和导航。该算法在实验性定制四旋翼飞行器上实现，该四旋翼飞行器使用机载视觉感应（即Intel RealSense R200）来检测障碍物的位置。我们在实验中展示了自动避撞和寻找目的地的能力，其中四旋翼飞机在未知的GPS拒绝的环境中导航。所有反馈测量值均从机载传感器获得。新的制导和控制算法使用非线性内环姿态控制器。非线性中环速度控制器；椭圆形势场外环引导算法，用于避免碰撞和寻找目的地。\（\ pm 90 ^ {\ circ} \）是闭环姿态动力学的局部指数稳定平衡，我们为每个姿态平衡量化吸引区域。