Anton Kolomeytsev

Skolkovo Institute of Science and Technology

Papers

Total Citations

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About

Anton Kolomeytsev is a robotics researcher specializing in visual Simultaneous Localization and Mapping (SLAM) for mobile robots, with a particular focus on multi-camera systems and computational efficiency. His most cited work, "MuCaSLAM: CNN-Based Frame Quality Assessment for Mobile Robot with Omnidirectional Visual SLAM" (2022, 11 citations), introduces an innovative intermediate processing layer that leverages convolutional neural networks to assess frame quality before feeding data into the SLAM pipeline. This approach significantly improves both computational efficiency and robustness in resource-constrained mobile robots equipped with multiple omnidirectional cameras. By filtering out low-quality frames, Kolomeytsev's method reduces computational overhead while maintaining mapping accuracy—a critical advancement for real-time autonomous navigation. His work addresses the fundamental challenge of balancing limited onboard processing power with the demanding requirements of visual SLAM in dynamic environments. This contribution is particularly valuable for applications in robotics, autonomous vehicles, and drone navigation, where reliable spatial awareness must be achieved with minimal latency and energy consumption.