Adi Sujiwo
Papers
3
Total Citations
129
H-Index
3
About
Adi Sujiwo is a leading researcher in autonomous robot navigation, with a focus on open-source planning and vision-based localization. His major contributions include the development of "OpenPlanner," an open-source integrated planner for mobile robots operating in highly dynamic environments. This planner, detailed in his most-cited paper (81 citations), combines global path planning, behavior state generation, and local planning, making it a cornerstone for accessible autonomous navigation research. Sujiwo has also advanced monocular vision-based localization, particularly through his work in the Tsukuba Challenge, a real-world robot competition. His 2016 paper (39 citations) introduced a method using ORB-SLAM with LIDAR-aided mapping to achieve robust localization in complex outdoor settings, while his 2017 follow-up (9 citations) improved coverage and accuracy by building custom visual vocabularies. These contributions demonstrate his ability to bridge theoretical algorithms with practical, real-world deployment, significantly impacting the field of autonomous robotics.
Research Focus
Key Achievements
Top Papers
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