Papers

7

Total Citations

49

H-Index

4

About

Akira Kojima is a leading researcher in autonomous driving systems, with a primary focus on FPGA-based robot car implementations. His work centers on developing real-time autonomous driving solutions using System-on-Chip (SoC) FPGAs, particularly Xilinx UltraScale+ MPSoC and Zynq platforms. Kojima’s major contributions include the design and implementation of lane-keeping systems using Convolutional Neural Networks (CNN) for online learning of steering control from real-time images, enabling autonomous navigation even on roads with missing or unclear lane markings. His research has been recognized through multiple FPGA design competitions (FPT 2018, 2019, 2021), where his robot car implementations demonstrated practical autonomous driving capabilities. With over 49 total citations across his published works, Kojima’s most impactful papers have each garnered 11-12 citations, establishing his reputation in the field. His 2023 work on persistent coverage control for mobile robots in complex environments extends his expertise beyond autonomous driving to multi-robot systems. Notably, Kojima’s early career included pioneering work on magnetic fluid-based attitude detectors, showcasing his long-standing commitment to robotics and sensor technology innovation.

Research Focus

Key Achievements

4
H-Index
7
Papers
49
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Autonomous Driving System implemented on Robot Car using SoC FPGA
12 citations · 2021
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Hiroshima City University, Tokyo Metropolitan University, Kanazawa Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago