Reiichiro Nakano
Papers
4
Total Citations
53
H-Index
4
About
Reiichiro Nakano is a pioneering researcher in the field of multi-agent robotics, with a primary focus on the control, coordination, and intelligence of quadrotor unmanned aerial vehicle (UAV) swarms. His work addresses fundamental challenges in swarm robotics, including real-time obstacle avoidance, collective aggregation, and decentralized communication. Nakano’s most influential contribution is his 2017 paper on obstacle avoidance using artificial potential fields, which has garnered 24 citations and provides a robust framework for enabling quadrotor swarms to navigate dynamic environments without collisions. He also introduced a novel genetic algorithm approach for swarm centroid tracking (14 citations), allowing a swarm to collectively encircle and follow a moving target. Further advancing the field, Nakano optimized decentralized information dissemination in swarms using genetic algorithms (8 citations), tackling the critical problem of limited situational awareness in distributed systems. His innovative application of Smoothed Particle Hydrodynamics (SPH) to model swarm aggregation (7 citations) demonstrates a unique interdisciplinary approach, treating each UAV as a fluid particle to achieve emergent, scalable behaviors. Nakano’s work is essential reading for anyone interested in the intersection of evolutionary computation, control theory, and autonomous aerial robotics.
Research Focus
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Top Papers
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