Anton Egorov

TL;DR: SeqSphereVLAD as mentioned in this paper is a lightweight 3D place recognition method, which is capable of recognizing places from a previous trajectory regardless of the viewpoint and the temporary observation differences, and it can achieve above 95% average recall for the best match with only 18% inference time of PointNet-based place recognition methods.

TL;DR: A novel lightweight 3-D place recognition and fast sequence matching method, capable of recognizing places from a previous trajectory regardless of viewpoints and temporary observation differences, is proposed, which outperforms the relative state of the art.

TL;DR: A LocoGear, a novel algorithm for locomotion of UAV equipped with the robotic landing gear, is proposed based on feedforward control that proves the capability of landing gear to move along the desired trajectory.

TL;DR: PSE-Match, a viewpoint-free place recognition method based on parallel semantic analysis of isolated semantic attributes from 3D point-cloud models, which incorporates a divergence place learning network to capture different semantic attributes parallelly through the spherical harmonics domain.

TL;DR: Zhang et al. as mentioned in this paper proposed a viewpoint-free place recognition method based on parallel semantic analysis of isolated semantic attributes from 3D point-cloud models, which is called PSE-Match, which incorporates a divergence place learning network to capture different semantic attributes parallelly through the spherical harmonics domain.