Flight with Limited Field of View: A Parallel and Gradient-free Strategy for Micro Aerial Vehicle

Abstract

In this paper, a parallel and gradient-free strategy is presented for autonomous navigation of a quadrotor with a limited field of view (FOV). The FOV constraint is nonlinear and non-continuous in general and involves higher order dynamics of the vehicle. Planning problems with such constraints are difficult to solve, especially with the realtime requirement. The proposed method first constructs an environment map by integrating the measurement of a limited-FOV sensor in a parallel process. Based on the map, it then selects a feasible local goal from a global path and generates a constraint-free nominal control sequence. Finally, a stochastic optimal control problem is solved to satisfy the limited FOV constraint, the dynamic constraint, the dynamic constraint, and the collision-free conditions at the same time. The objective functions are non-linear and non-continuous and involves dynamic of MAV. A parallel gradient-free algorithm is used to address these problems. Both the sensing and planning problems are solved parallelly on a light-weight Graphics Processing Unit (GPU). The effectiveness of the proposed strategy is demonstrated through both simulation and real flight experiments.