Robot navigation using modified SLAM procedure based on depth image reconstruction

A. Zelenskii; N. Gapon; V. Voronin; E. Semenishchev; V. Serebrenny; Y. Cen

doi:10.1117/12.2600736

12 September 2021 Robot navigation using modified SLAM procedure based on depth image reconstruction

A. Zelenskii, N. Gapon, V. Voronin, E. Semenishchev, V. Serebrenny, Y. Cen

Proceedings Volume 11870, Artificial Intelligence and Machine Learning in Defense Applications III; 118700H (2021) https://doi.org/10.1117/12.2600736
Event: SPIE Security + Defence, 2021, Online Only

Abstract

In modern mobile robots, technologies are used that make it possible to build the most optimal path for its movement. This uses simultaneous navigation and mapping techniques known as SLAM. A problem with all depth mapping methods is the presence of lost areas. This problem occurs due to poor lighting, mirrored surfaces of objects, or the fine-grained surface of materials, which makes it impossible to measure depth information. As a result, the effect of overlapping objects appears, which makes it impossible to distinguish one object from another, or an increase in the object's boundaries (obstacles) occurs. It is possible to solve this problem with the help of image reconstruction methods. This article presents an approach based on a modified algorithm for finding similar blocks using the autoencoder-learned local image descriptor for image inpainting. For this purpose, we learn the descriptors using a convolutional autoencoder network. The proposed algorithm also uses the concepts of a sparse representation of quaternions, which uses a new gradient to calculate the priority function by integrating the structure of quaternions with the saliency map. Compared with state-of-the-art techniques, the proposed algorithm provides plausible restoration of the depth map from multimodal images, making them a promising tool for robot navigation and defence applications. Analysis of the processing results shows that the proposed method allows you to correctly reconstruct the boundaries of objects in the image and the depth map, which is a prerequisite for increasing the accuracy of robot navigation.

Conference Presentation

Citation Download Citation

A. Zelenskii, N. Gapon, V. Voronin, E. Semenishchev, V. Serebrenny, and Y. Cen "Robot navigation using modified SLAM procedure based on depth image reconstruction", Proc. SPIE 11870, Artificial Intelligence and Machine Learning in Defense Applications III, 118700H (12 September 2021); https://doi.org/10.1117/12.2600736

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