3D Map Exploration via Learning Submodular Functions in the Fourier Domain

Bing Xian Lu, Kuo Shih Tseng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

3D map exploration is one of key technologies in robotics. However, finding an optimal exploration path is a challenge since the environment is unknown. This research proposed the submodular exploration (SE) algorithm to enable an unmanned aerial vehicle (UAV) to explore 3D environments. The algorithm learns the submodular function in the Fourier domain and reconstructs the submodular function in the spatial domain via the compressed sensing techniques. Since the objective function of spatial exploration is reformulated as a maximizing submodular function with path constraints, greedy algorithms can achieve \frac{1}{2} (1-e-1) of the optimum. Experiments conducted with this algorithm demonstrate that the UAV can explore more voxels in the environments than the benchmark approach.

Original languageEnglish
Title of host publication2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1199-1205
Number of pages7
ISBN (Electronic)9781728142777
DOIs
StatePublished - Sep 2020
Event2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020 - Athens, Greece
Duration: 1 Sep 20204 Sep 2020

Publication series

Name2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020

Conference

Conference2020 International Conference on Unmanned Aircraft Systems, ICUAS 2020
Country/TerritoryGreece
CityAthens
Period1/09/204/09/20

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