Daito Sakai

Papers

Total Citations

111

H-Index

About

Daito Sakai is a leading figure in multi-robot systems, specializing in decentralized control, swarm robotics, and connectivity preservation in complex environments. His research addresses fundamental challenges in coordinating multiple mobile agents without relying on centralized communication or explicit environmental distinctions. Sakai’s most influential work, “Leader–Follower Navigation in Obstacle Environments While Preserving Connectivity Without Data Transmission” (2017, 57 citations), introduces a groundbreaking control method that maintains sensing network connectivity during navigation without requiring data exchange between robots—a significant departure from traditional approaches. Equally impactful is his 2016 paper “Flocking for Multirobots Without Distinguishing Robots and Obstacles” (54 citations), which proposes a flocking algorithm that eliminates the need for robots to differentiate between peers and obstacles, enabling simpler and more robust implementation in real-world settings. These contributions have been widely cited for their practical elegance and theoretical depth, offering scalable solutions for applications in search-and-rescue, environmental monitoring, and autonomous exploration. Sakai’s work continues to influence the next generation of roboticists, demonstrating that minimal sensing and communication can achieve sophisticated collective behavior.