Sakai Hideaki

Papers

Total Citations

H-Index

About

Dr. Hideaki Sakai is a robotics researcher whose work focuses on motion planning and autonomous manipulation for articulated robotic systems, particularly multi-degree-of-freedom (DOF) manipulators. His most cited contribution, "Motion Planning for 6 DOF Robot Arm Based on Maze-searching" (2010), introduces a novel approach that adapts the maze-searching paradigm to robotic arm pathfinding. By modifying the Closest Point First Search (CPFS) algorithm—inspired by Lumelsky’s Bug2 algorithm—with a Footprint Avoidance Protocol (FAP), Sakai developed a computationally efficient method for generating collision-free trajectories in complex environments. This work addresses a fundamental challenge in robotics: enabling high-DOF arms to navigate cluttered spaces without exhaustive computation. While his citation count (4) reflects a specialized, early-career contribution, the paper’s significance lies in its algorithmic elegance and practical applicability to industrial and service robotics. Sakai’s research bridges theoretical path planning with real-world constraints, offering a scalable solution for autonomous manipulation tasks. His work continues to inform advancements in robot autonomy, particularly in scenarios requiring rapid, adaptive motion planning.