  Autonomous exploration is one of the important parts to achieve the fast
autonomous mapping and target search. However, most of the existing methods are
facing low-efficiency problems caused by low-quality trajectory or
back-and-forth maneuvers. To improve the exploration efficiency in unknown
environments, a fast autonomous exploration planner (FAEP) is proposed in this
paper. Different from existing methods, 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 in
the asymmetric traveling salesman problem (ATSP). Then, according to the
exploration sequence and the distribution of frontiers, an adaptive yaw
planning method is proposed to cover more frontiers by yaw change during an
exploration journey. In addition, to increase the speed and fluency of flight,
a dynamic replanning strategy is also adopted. We present sufficient comparison
and evaluation experiments in simulation environments. Experimental results
show the proposed exploration planner has better performance in terms of flight
time and flight distance compared to typical and state-of-the-art methods.
Moreover, the effectiveness of the proposed method is further evaluated in
real-world environments.
