An adaptive path replanning method for coordinated operations of drone in dynamic urban environments

Abstract

Drones should be allowed to respond to dynamic urban environments and self-adjust their paths, safely and efficiently. Existing studies fail to develop a comprehensive approach to deal with drone encountering various dynamic changes over the course of flying. In this paper, an adaptive path replanning (APReP) method is proposed in discrete urban environments by considering the features of different types of dynamic changes, and the coordination among drones as well. First, various dynamic changes are concluded into three types. Three strategies are developed to conduct the path replanning for a single-drone operation under different combinations of dynamic changes. As the path replanning is extended to the operation involving multiple drones, the orders of planning are determined by task priority, path planning strategy and competition mechanism. A discrete rapidly-exploring random tree (DRRT) algorithm is presented to generate the path considering the characteristic of discrete urban environments. Simulation results demonstrate that DRRT algorithm is suitable for the path replanning problems considered, and the three proposed path replanning strategies are valid to cope with the corresponding types of dynamic change. Compare to other two algorithms, APReP algorithm is more efficient in large-scale problems with a number of dynamic changes.