Artem Bazhenov
Papers
4
Total Citations
26
H-Index
3
About
Artem Bazhenov is a pioneering researcher at the intersection of robotics, artificial intelligence, and human-robot interaction, with a focus on quadruped robots and large language models (LLMs). His work centers on making robots more autonomous, communicative, and useful in real-world settings, particularly for assistive technologies. Bazhenov’s major contributions include the development of **CognitiveDog** (16 citations), a groundbreaking system that integrates a Large Multimodal Model (LMM) into a quadruped robot, enabling it to understand verbal commands, manipulate objects, and physically interact with its environment. He also introduced **DogSurf** (5 citations), which uses GRU-based surface recognition to help visually impaired individuals navigate safely by detecting slippery surfaces and providing haptic feedback. His **LLM-MARS** system (3 citations) was the first to leverage LLMs for dynamic dialogue and behavior tree generation in multi-agent robot teams, allowing robots to interpret operator commands and respond informatively. Additionally, **HyperSurf** (2 citations) advances surface recognition through a novel single-leg setup and real-to-sim transfer learning. Bazhenov’s work is notable for its practical, human-centered applications, bridging advanced AI with tangible robotic assistance.
Research Focus
Key Achievements
Top Papers
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