James V. Johnson

Papers

Total Citations

1,198

H-Index

About

James V. Johnson is a leading researcher in underwater robotics and visual-inertial state estimation, with a focus on enabling autonomous navigation in challenging subsea environments. His most influential work, with over 1,000 citations, stems from a comprehensive evaluation of state estimation techniques presented at the 2019 IEEE/RSJ IROS conference, which critically assessed the performance of visual and visual-inertial algorithms beyond typical indoor and urban settings. Johnson’s key contributions include experimentally comparing open-source visual-inertial algorithms specifically for underwater domains, demonstrating how these methods perform under the unique constraints of low visibility, dynamic lighting, and unstructured terrain. His research has advanced coverage path planning for autonomous underwater vehicles, notably through human diver-inspired visual navigation strategies for surveying complex structures like shipwrecks. By bridging the gap between terrestrial state estimation and underwater robotics, Johnson has provided foundational benchmarks and practical solutions that inform both academic research and real-world marine exploration. His work is essential reading for students and engineers developing robust autonomous systems for extreme environments.