Abstract
This paper presents a human-like motion decision-making method for unmanned aerial vehicles(UAVs)navigating in trap envi-ronments.We proposed a space partitioning method based on sampling and consistency control to conduct a preliminary analysis of the indoor environment based on architectural blueprints.This method reduces the dimensionality of the path planning problem,thereby enhancing the efficiency.Then,we designed a target-switching logic for the dynamic window approach.This improve-ment endows the UAV with the capability of both real-time obstacle avoidance and global navigation,enhancing the efficiency of the UAV in flying to task spots indoors.Additionally,by applying human-like methods of batch distance perception and obstacle perception to this scheme,we have further enhanced the robustness and efficiency of path decisions.Finally,considering the scenario of high-rise fire rescue,we conducted simulation verification.It demonstrates that our scheme enhances the efficiency and robustness of path planning.
基金项目
国家自然科学基金(62033003)
国家自然科学基金(62373113)
国家自然科学基金(U23A20341)
广东省自然科学基金(2023A1515011527)
广东省自然科学基金(2022A1515011506)
维普
万方数据