4 citations · 7 across the 10 of their papers we have counts for
11 papers
LocoNeRF: A NeRF-based Approach for Local Structure from Motion for Precise Localization
Artem Nenashev, Mikhail Kurenkov, Andrei Potapov +3
Visual localization is a critical task in mobile robotics, and researchers are continuously developing new approaches to enhance its efficiency. In this article, we propose a novel…
DNFOMP: Dynamic Neural Field Optimal Motion Planner for Navigation of Autonomous Robots in Cluttered Environment
Maksim Katerishich, Mikhail Kurenkov, Sausar Karaf +2
Motion planning in dynamically changing environments is one of the most complex challenges in autonomous driving. Safety is a crucial requirement, along with driving comfort and sp…
Hierarchical Visual Localization Based on Sparse Feature Pyramid for Adaptive Reduction of Keypoint Map Size
Andrei Potapov, Mikhail Kurenkov, Pavel Karpyshev +4
Visual localization is a fundamental task for a wide range of applications in the field of robotics. Yet, it is still a complex problem with no universal solution, and the existing…
SwipeBot: DNN-based Autonomous Robot Navigation among Movable Obstacles in Cluttered Environments
Nikolay Zherdev, Mikhail Kurenkov, Kristina Belikova +1
In this paper, we propose a novel approach to wheeled robot navigation through an environment with movable obstacles. A robot exploits knowledge about different obstacle classes an…
LiePoseNet: Heterogeneous Loss Function Based on Lie Group for Significant Speed-up of PoseNet Training Process
Mikhail Kurenkov, Ivan Kalinov, Dzmitry Tsetserukou
Visual localization is an essential modern technology for robotics and computer vision. Popular approaches for solving this task are image-based methods. Nowadays, these methods ha…
MeSLAM: Memory Efficient SLAM based on Neural Fields
Evgenii Kruzhkov, Alena Savinykh, Pavel Karpyshev +4
Existing Simultaneous Localization and Mapping (SLAM) approaches are limited in their scalability due to growing map size in long-term robot operation. Moreover, processing such ma…
MuCaSLAM: CNN-Based Frame Quality Assessment for Mobile Robot with Omnidirectional Visual SLAM
Pavel Karpyshev, Evgeny Kruzhkov, Evgeny Yudin +6
In the proposed study, we describe an approach to improving the computational efficiency and robustness of visual SLAM algorithms on mobile robots with multiple cameras and limited…
CloudVision: DNN-based Visual Localization of Autonomous Robots using Prebuilt LiDAR Point Cloud
Evgeny Yudin, Pavel Karpyshev, Mikhail Kurenkov +4
In this study, we propose a novel visual localization approach to accurately estimate six degrees of freedom (6-DoF) poses of the robot within the 3D LiDAR map based on visual data…
DarkSLAM: GAN-assisted Visual SLAM for Reliable Operation in Low-light Conditions
Alena Savinykh, Mikhail Kurenkov, Evgeny Kruzhkov +4
Existing visual SLAM approaches are sensitive to illumination, with their precision drastically falling in dark conditions due to feature extractor limitations. The algorithms curr…
UltraBot: Autonomous Mobile Robot for Indoor UV-C Disinfection
Stepan Perminov, Nikita Mikhailovskiy, Alexander Sedunin +4
The paper focuses on the development of the autonomous robot UltraBot to reduce COVID-19 transmission and other harmful bacteria and viruses. The motivation behind the research is…
Comparison of modern open-source visual SLAM approaches
Dinar Sharafutdinov, Mark Griguletskii, Pavel Kopanev +5
SLAM is one of the most fundamental areas of research in robotics and computer vision. State of the art solutions has advanced significantly in terms of accuracy and stability. Unf…