Abstract
Autonomous exploration of unknown environments is the basis for mobile robots in applications like rescue and industrial inspection. The critical capability for autonomous exploration is the determination of the next exploration point. In this paper, we proposed an autonomous exploration strategy for 3D multi-layer environments. The ML-SKiMap structure is presented to store and retrieve the map with the layer information, and the stability and obstacle collision situation are analyzed to check the traversability of each voxel in ML-SKiMap. Furthermore, a cost function in terms of exploration information entropy, layer weight, and navigation cost is adopted to evaluate the exploration performance, and the optimal next exploration point is selected with minimum exploration cost. The experiments in simulation and practice demonstrate that the proposed method can explore multi-layer environments effectively.
Sponsored by Natural Science Foundation of Shanghai, Grant No. 20ZR1419100.
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Yang, Y., Zhang, J., Qian, W., Geng, H., Xie, Y. (2023). Autonomous Exploration for Mobile Robot in Three Dimensional Multi-layer Space. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14274. Springer, Singapore. https://doi.org/10.1007/978-981-99-6501-4_22
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