Anton Grigoryev

Institute for Information Transmission Problems

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About

Anton Grigoryev is a robotics researcher specializing in autonomous navigation, computer vision, and real-time object detection. His work bridges the gap between efficient machine learning algorithms and practical robotic systems, with a focus on enabling robots to perceive and localize themselves in complex environments. His most cited paper, "Application of Random Ferns for non-planar object detection" (2015, 6 citations), demonstrates a key contribution: adapting the Random Ferns algorithm for rapid, real-time object detection in autonomous ground robots, leveraging fast keypoint matching for robust performance. He further advanced indoor robot localization in "Edge detection based mobile robot indoor localization" (2019, 5 citations), where he fused visual edge detection with onboard motion sensors—such as wheel speed and yaw rate sensors—to achieve precise pose estimation against building schematics. Most recently, his 2023 work on "Prior Distribution Refinement for Reference Trajectory Estimation" introduces a novel method for generating accurate reference trajectories in Monte Carlo-based localization, enabling fairer benchmarking of positioning algorithms. Though his citation counts are modest, Grigoryev’s contributions are foundational for practical, low-cost robotic navigation systems, offering reproducible solutions for real-world deployment in constrained environments.