Papers
6
Total Citations
80
H-Index
4
About
Pavel Kopanev is a robotics researcher whose work spans visual SLAM, tactile perception, and underwater object detection, with a focus on enabling robots to better understand and interact with their environments. His most cited paper, "Comparison of modern open-source Visual SLAM approaches" (2023, 46 citations), provides a critical benchmark for the robotics community, evaluating state-of-the-art solutions in accuracy and stability—a foundational resource for researchers and practitioners alike. Kopanev’s innovative contributions include "DogTouch" (2022, 21 citations), where he developed a CNN-based system for quadruped robots to recognize surface textures using high-density tactile sensors, mimicking animal locomotion to improve terrain adaptation. He also explored "DeepXPalm" (2022), a haptic display for palm-worn devices that enhances telemanipulation of deformable objects through tactile pattern recognition, and compared classical versus neural network approaches for underwater robotics competitions (2022, 5 citations). With over 80 total citations, Kopanev’s work bridges perception and control, advancing robust locomotion and dexterous manipulation in challenging environments. His achievements highlight a commitment to open-source solutions and practical robotics, making him a notable figure in the field.
Research Focus
Key Achievements
Top Papers
- 1Comparison of modern open-source Visual SLAM approaches46 citations · 2023
- 2
- 3
- 4Comparison of modern open-source visual SLAM approaches4 citations · 2021
- 5
- 6