In order to reduce the influence of various interference factors in the process of UAV autonomous navigation mission, increase the stability, reduce the risk of flight test and save costs, this paper analyzes the UAV and sensor models for the needs of UAV autonomous navigation task in the building space environment, and constructs a flight scene library for the building space environment. A distributed simulation platform is built to ensure that UAV can effectively complete the verification and evaluation of relevant algorithms in the simulation environment.

This paper proposes a distributed collaborative complete coverage path planning (CCPP) algorithm based on a heuristic method to solve a CCPP problem for multiple agents in an unknown environment. Based on the relationship between path length, energy consumption and number of turns, the algorithm instructs the agents to autonomously plan their respective paths in real time by giving the priority of directions. Simulation experiments show that the proposed CCPP algorithm can guarantee efficient collision-free complete coverage compared with related approaches.