FAEP: Fast Autonomous Exploration Planner for UAV Equipped with Limited FOV Sensor

Abstract

Autonomous exploration is one of the important parts to achieve the autonomous operation of Unmanned Aerial Vehicles (UAVs). To improve the efficiency of the exploration process, a fast and autonomous exploration planner (FAEP) is proposed in this paper. We firstly design a novel frontiers exploration sequence generation method to obtain a more reasonable exploration path, which considers not only the flight-level but frontier-level factors into TSP. According to the exploration sequence and the distribution of frontiers, a two-stage heading planning strategy is proposed to cover more frontiers by heading change during an exploration journey. To improve the stability of path searching, a guided kinodynamic path searching based on a guiding path is devised. In addition, a dynamic start point selection method for replanning is also adopted to increase the fluency of flight. We present sufficient benchmark and real-world experiments. Experimental results show the superiority of the proposed exploration planner compared with typical and state-of-the-art methods.

A self-rotating, single-actuated UAV with extended sensor field of view for autonomous navigation

“…An existing issue for UAVs is that the small field of view (FoV) of these sensors severely limits the UAV's perception capability and task efficiency. Although many efforts have been made to deal with the constraints in applications induced by narrow or limited FoVs (1)(2)(3)(4)(5), a larger FoV is still a better solution that not only reduces task time by observing the environment more efficiently (6) but also enhances the UAV safety in the wild by perceiving dynamic obstacles (e.g., birds) approaching from an unknown direction (7).…”