Abstract
This paper proposes a robot autonomous exploration algorithm based on multi-resolution fields to solve the problems of low efficiency, high path repetition, and limited environmental adaptability in complex environments. First, OctoMap’s layered architecture is used to create a multi-resolution voxel map. A coarse-fine dual stage is then used to detect frontiers and balance point numbers. Second, polar coordinate sampling is utilized to avoid the sampling points being too concentrated in the center of the circle, and the scoring function is constructed by combining the distance decay function to prevent the robot from repeating the search. Finally, Monte Carlo integration’s gain calculation method is introduced to eliminate step errors caused by discretization and improve gain calculation accuracy. Simulation experiments are carried out in different environments, and the data prove that the method in this paper is better than the comparison algorithm in terms of moving distance, running time and exploration efficiency. The results show that the algorithm proposed in this paper effectively improves the robot’s autonomous exploration performance in unknown complex environments and provides a new solution for practical applications.
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The accessibility of the raw data and code utilized in this study is restricted. Should further experimental data be required related to the results, interested parties should contact the corresponding author.
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Funding
This work was supported in part by the Henan Province Key Research and Development Project (Grant No. 241111213000), in part by the Scientific Research Team Plan of Zhengzhou University of Aeronautics (Grant Nos. 23ZHTD01007, 24ZHTD01001), in part by the Zhengzhou University of Aeronautics Research Platform Open Fund Project (Grant No. ZHKF-230204), in part by the Henan Provincial Key Technology Research and Development Program (Grant Nos. 232102220025, 252102210023), in part by the Henan Key Laboratory of General Aviation Technology, in part by the Henan Province Collaborative Innovation Center of Aeronautics and Astronautics Electronic Information Technology, and in part by the Henan Province Special and Urgent Subject Group of Aeronautical and Astronautical Intelligent Engineering.
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Z.Z. developed the methodology, performed the simulations, and drafted the main text of the manuscript. L.X. and Y.Z. reviewed and edited the manuscript and evaluated the simulation results. G.Z. and Y.C. organized the data and managed the project. The final manuscript was reviewed and approved by all authors.
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Zhai, Z., Xu, L., Zhang, Y. et al. Multi-resolution field-based algorithm for autonomous robot exploration. Sci Rep (2026). https://doi.org/10.1038/s41598-026-46119-3
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DOI: https://doi.org/10.1038/s41598-026-46119-3
