Anastasia Gaydashenko
Papers
1
Total Citations
8
H-Index
1
About
Anastasia Gaydashenko is a leading researcher in the intersection of artificial intelligence and robotics, with a primary focus on autonomous navigation in dynamic human environments. Her work addresses the critical challenge of enabling robots to move efficiently and safely through crowded spaces—a problem that requires balancing speed, collision avoidance, and social compliance. In her most influential study, "A Comparative Evaluation of Machine Learning Methods for Robot Navigation Through Human Crowds" (2018, 8 citations), Gaydashenko systematically benchmarked deep learning, reinforcement learning, and traditional pathfinding algorithms, revealing the trade-offs between computational efficiency and safety in real-world crowd scenarios. This foundational work has guided subsequent developments in socially-aware navigation systems. Beyond her core contributions, Gaydashenko is recognized for advancing the integration of predictive human motion modeling with robot decision-making, a key step toward seamless human-robot coexistence. Her research continues to shape the design of autonomous systems in public spaces, from delivery robots to assistive technologies, making her a notable voice in the robotics and AI communities.
Research Focus
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Top Papers
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