Efficient and High Path Quality Autonomous Exploration and Trajectory Planning of UAV in an Unknown Environment

ISPRS International Journal of Geo-Information

Zhenbao Liu¹  Jinbiao Yuan¹  Li Yan²  Leyang Zhao²  Xiao Hu² 

[1] School of Civil Aviation, Northwestern Polytechnical University, Xi’an 710068, China;School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China;

关键词: unmanned aerial vehicles;    autonomous exploration;    path planning;    octrees;    frontier-based exploration;    rapidly exploring random tree;   

DOI  :  10.3390/ijgi10100631

来源: DOAJ

【 摘 要 】

The ability of an autonomous Unmanned Aerial Vehicle (UAV) in an unknown environment is a prerequisite for its execution of complex tasks and is the main research direction in related fields. The autonomous navigation of UAVs in unknown environments requires solving the problem of autonomous exploration of the surrounding environment and path planning, which determines whether the drones can complete mission-based flights safely and efficiently. Existing UAV autonomous flight systems hardly perform well in terms of efficient exploration and flight trajectory quality. This paper establishes an integrated solution for autonomous exploration and path planning. In terms of autonomous exploration, frontier-based and sampling-based exploration strategies are integrated to achieve fast and effective exploration performance. In the study of path planning in complex environments, an advanced Rapidly Exploring Random Tree (RRT) algorithm combining the adaptive weights and dynamic step size is proposed, which effectively solves the problem of balancing flight time and trajectory quality. Then, this paper uses the Hermite difference polynomial to optimization the trajectory generated by the RRT algorithm. We named proposed UAV autonomous flight system as Frontier and Sampling-based Exploration and Advanced RRT Planner system (FSEPlanner). Simulation performs in both apartment and maze environment, and results show that the proposed FSEPlanner algorithm achieves greatly improved time consumption and path distances, and the smoothed path is more in line with the actual flight needs of a UAV.

【 授权许可】

Unknown