Andrey Priorov
Papers
7
Total Citations
30
H-Index
4
About
Andrey Priorov is a robotics researcher specializing in autonomous navigation, sensor fusion, and computer vision for mobile robots. His work centers on solving the Simultaneous Localization and Mapping (SLAM) problem, developing algorithms that enable robots to build maps of unknown environments while tracking their own position. Priorov has made key contributions to multi-sensor SLAM, notably integrating laser scanning systems with fisheye cameras using Extended Kalman Filters (EKF-SLAM, 10 citations), and advancing LIDAR-based odometry for contour analysis of surroundings. His research also extends to real-time robot control, including color pattern recognition for robosoccer applications, and indoor navigation systems that leverage monocular cameras and color beacons for obstacle detection. More recently, Priorov has explored multimodal biometric identification using convolutional neural networks for facial and speech recognition. His most-cited work, the EKF-SLAM algorithm combining laser and fisheye camera data, demonstrates his focus on practical, real-world robotic navigation solutions. With a career spanning over a decade, Priorov’s research continues to push the boundaries of autonomous mobile robotics, offering robust approaches to spatial perception and environmental understanding.
Research Focus
Key Achievements
Top Papers
- 1The Algorithm of EKF-SLAM Using Laser Scanning System and Fisheye Camera10 citations · 2019
- 2
- 3The LIDAR Odometry in the SLAM4 citations · 2018
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- 5
- 6Self-localization of mobile robot in unknown environment2 citations · 2015
- 7