Papers
25
Total Citations
503
H-Index
13
About
Yu Bo is a prominent researcher at the intersection of robotics, embedded systems, and hardware acceleration, whose work has significantly advanced the field of robotic computing. His research focuses on designing efficient hardware architectures—particularly FPGA-based systems—to meet the demanding computational requirements of autonomous machines, including self-driving vehicles, drones, and logistic robots. Among his most impactful contributions is a comprehensive survey of FPGA-based robotic computing (112 citations), which has become an essential reference for the field. His π-series of works introduced specialized hardware accelerators for SLAM and bundle adjustment, tackling the dual challenges of computational intensity and real-time performance on resource-constrained platforms. His LoPECS system (67 citations) demonstrated how heterogeneous edge computing architectures can enable multiple autonomous driving services simultaneously on affordable embedded hardware. Beyond individual accelerators, Yu Bo has developed generalized frameworks—Archytas and ORIANNA—for automatically synthesizing and optimizing accelerators for robotic applications, addressing scalability challenges that manual design approaches cannot meet. His work on sensor synchronization further reflects his holistic approach to autonomous systems engineering. Collectively, his publications have garnered nearly 400 citations, establishing him as a leading voice in hardware-efficient robotic computing.
Research Focus
Key Achievements
Top Papers
- 1A Survey of FPGA-Based Robotic Computing112 citations · 2021
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- 5π-SoC: Heterogeneous SoC Architecture for Visual Inertial SLAM Applications28 citations · 2018
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- 8Robotic Computing on FPGAs22 citations · 2021
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