Irina Vatamaniuk
Papers
11
Total Citations
98
H-Index
4
About
Irina Vatamaniuk is a leading researcher in swarm robotics and modular robotic systems, whose work has significantly advanced the fields of self-reconfiguration, swarm aggregation, and autonomous navigation. Her most influential paper, "Self-reconfiguration algorithms for robotic systems" (2018, 34 citations), introduced an original decomposition-based approach to reconfiguration planning for chain-type robots, addressing a fundamental challenge in modular robotics. Her survey on robot swarm aggregation (2017, 23 citations) systematically analyzed bio-inspired methods for coordinating autonomous robots, establishing key hardware and algorithmic requirements. Vatamaniuk's work on convex shape generation (2016, 12 and 9 citations) developed collision-free motion planning algorithms for homogeneous robot swarms, enabling efficient spatial reconfiguration. She has also pioneered the application of deep reinforcement learning to modular robot reconfiguration (2021) and reinforcement learning for navigation using LIDAR data (2019). Her research on human-machine interfaces for group control of agricultural robots (2022) demonstrates the practical impact of her work. With over 90 total citations, Vatamaniuk's contributions continue to shape the theoretical foundations and practical implementations of swarm and modular robotics.
Research Focus
Key Achievements
Top Papers
- 1Self-reconfiguration algorithms for robotic systems34 citations · 2018
- 2Survey of Methods and Algorithms of Robot Swarm Aggregation23 citations · 2017
- 3Automatic control of robotic swarm during convex shape generation12 citations · 2016
- 4Convex Shape Generation by Robotic Swarm9 citations · 2016
- 5
- 6Review of the Methods and Algorithms of a Robot Swarm Aggregation4 citations · 2017
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- 9
- 10A*-Based Path Planning Algorithm for Swarm Robotics2 citations · 2020