Minas Dasygenis
Papers
24
Total Citations
191
H-Index
9
About
Minas Dasygenis is a robotics and autonomous systems researcher whose work spans mobile robot navigation, unmanned ground vehicles (UGVs), warehouse automation, and educational robotics. His research consistently addresses real-world challenges in path planning, task allocation, and intelligent robot behavior, making him a notable contributor to both applied and theoretical robotics. Dasygenis has made significant strides in optimizing navigation algorithms, particularly refining the A* algorithm to produce smoother, more energy-efficient paths for agricultural and warehouse robotics — work that has garnered over 34 and 10 citations respectively. His investigations into deep reinforcement learning for dynamic environment navigation further demonstrate a forward-looking approach to adaptive autonomous systems. In warehouse robotics, his algorithms for routing heterogeneous vehicle fleets and optimizing task allocation address critical scalability and efficiency challenges facing modern logistics. Beyond industrial applications, Dasygenis has explored the humanitarian potential of robotics, developing a cloud-connected humanoid robot designed to assist rescuers in hazardous pandemic-era environments. Equally notable is his commitment to education, leveraging robotics to cultivate environmental empathy in primary school students. With over 140 cumulative citations across his most prominent works, Dasygenis represents a versatile and socially conscious voice in contemporary robotics research.
Research Focus
Key Achievements
Top Papers
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- 9An algorithm for routing heterogeneous vehicles in robotized warehouses9 citations · 2019
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