Papers

42

Total Citations

788

H-Index

16

About

Yusuke Tamura is a robotics researcher whose work spans autonomous mobile robotics, human-robot coexistence, humanoid systems, and environmental sensing. He is perhaps best known for his contributions to robot path planning, most notably his development of the Improved Artificial Potential Field-based Regression Search (Improved APF-based RS) method, which efficiently computes collision-free paths while eliminating the classic problems of local minima and oscillations in both static and dynamic environments. His 2012 paper on this topic has garnered 158 citations, establishing it as a landmark contribution to the field. Tamura has also made significant strides in human-robot coexistence, developing pedestrian behavior models that account for human intention and enable smooth, socially aware collision avoidance. His involvement in the DARwIn-OP open-platform humanoid robot project reflects a commitment to accessible research infrastructure, while his work on coupled oscillator-based gait stabilization demonstrates expertise in bipedal locomotion. More recently, Tamura has extended his reach into novel sensing domains, including 3D radiation source imaging using mobile robots and acoustic camera-based SLAM for dense underwater 3D mapping. With over 500 cumulative citations, his diverse yet cohesive body of work marks him as a versatile and influential figure in modern robotics research.

Research Focus

Key Achievements

16
H-Index
42
Papers
788
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
An efficient improved artificial potential field based regression search method for robot path planning
158 citations · 2012
📈 Most Prolific Year: 2011 (6 Papers)
🤝 Key Collaborators: 71
🏛 Institutions: Chuo University, The University of Tokyo, Tohoku University, University of Tsukuba, Chinese University of Hong Kong

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago