Cooperative Sensor-based Selective Graph Exploration Strategy for a Team of Quadrotors

Abstract

This paper proposes an exploration strategy in unknown environments for a team of quadrotor Unmanned Aerial Vehicles (UAVs). Based on the frontier information, the proposed strategy builds a roadmap of the explored area in form of a Sensor-based Selective Graph (SSG) using simple data trees of the frontier and the hub node only. In particular, the frontier data tree is utilized to consider the adjacent frontier sectors as one frontier sector, and the next target node is generated maximizing the coverage of frontiers at each movement of quadrotors. In addition, to expand the proposed strategy to the three dimensional (3D) workspace with quadrotors, a Multiple Flight Levels (MFL) approach is proposed to increase the efficiency of the exploration. Moreover, when a quadrotor reaches a dead end where no frontier exists, the efficient backtracking algorithm chooses the best path to backtrack efficiently with a graph map provided by the SSG. With these contributions, we successfully develop the frontier-based exploration strategy for multiple quadrotors, and performance of the overall approach is validated by numerical simulations and experiments.