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Partition and planning:A human-like motion decision for UAV in trap environment
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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.
path planningindoor environmentspacial partitionhigh-rise fire rescue
CHEN JinTao、ZHOU Qi、REN HongRu、LI HongYi
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School of Automation,Guangdong University of Technology,Guangzhou 510006,China
Provincial Key Laboratory of Intelligent Decision and Cooperative Control Guangdong University of Technology,Guangzhou 510006,China
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