Ken Sakurada

National Institute of Advanced Industrial Science and Technology

Papers

Total Citations

H-Index

About

Ken Sakurada is a leading researcher in robotics and computer vision, with a primary focus on sensor fusion and visual simultaneous localization and mapping (VSLAM). His work addresses critical challenges in autonomous systems, particularly the integration of LiDAR and camera data for robust perception. In his highly cited 2023 paper, "INF: Implicit Neural Fusion for LiDAR and Camera," Sakurada tackles the persistent difficulties of data representation differences and extrinsic calibration in sensor fusion, proposing an implicit neural approach that has already garnered 11 citations for its innovative solution. Earlier, his 2019 work "OpenVSLAM" revolutionized the field by creating a modular, library-style VSLAM framework designed for easy integration into third-party applications—a departure from conventional monolithic systems. This contribution, with 6 citations, has become a foundational tool for researchers and engineers developing augmented reality devices and autonomous robots. Sakurada’s work consistently bridges theoretical advances with practical usability, making him a pivotal figure in enabling more reliable and accessible autonomous navigation systems.