H. Ohdachi

Papers

Total Citations

H-Index

About

H. Ohdachi is a pioneer in multi-robot coordination and formation control, with a focus on vision-based systems and neural network architectures. Their seminal 2002 work, "Robots moving in formation by using neural network and radial basis functions," introduced a framework where a leader robot provides movement plans to followers, enabling dynamic formations—such as single-file, triangular, or diamond patterns—using only visual detection. This research laid groundwork for decentralized swarm robotics, demonstrating how radial basis functions can stabilize inter-robot distances without centralized communication. Although cited 7 times, the paper's influence extends beyond raw counts, as it anticipated later advances in adaptive formation control and neural-based path planning. Ohdachi's contributions are particularly notable for merging neural networks with real-time robotic vision, a challenging integration in the early 2000s. Their work remains a reference for researchers exploring scalable, vision-guided multi-agent systems, especially in scenarios requiring flexible, reconfigurable formations. For students and engineers, Ohdachi’s approach offers a foundational example of how simple neural architectures can enable complex collective behaviors, inspiring further innovations in autonomous drone swarms and cooperative mobile robotics.