Papers
2
Total Citations
9
H-Index
2
About
Jinho Yang is a robotics engineer whose research bridges the gap between novel mechanical design and efficient embedded intelligence for autonomous systems. His work centers on two key areas: the development of modular robotic platforms with enhanced degrees of freedom, and the acceleration of neural networks on resource-constrained hardware. Yang’s most notable contribution is the **extended coaxial spherical joint module (E-CoSMo)** , a novel mechanism that combines a coaxial spherical parallel mechanism with an additional universal joint to achieve three to four degrees of freedom. This design, published in 2018, lays the groundwork for more versatile and compact multi-DOF robotic platforms, enabling complex motion in confined spaces. In parallel, Yang is advancing the deployment of convolutional neural networks on autonomous mobile robots. His 2024 work, **“ACane,”** introduces an FPGA-based embedded vision platform that uses an innovative **accumulation-as-convolution packing** method. This technique efficiently leverages low-precision quantization and DSP packing, significantly improving the speed and energy efficiency of CNN inference on mobile robots. With a growing citation footprint, Yang’s dual focus on mechanical ingenuity and hardware-aware AI positions him as a rising contributor to the next generation of agile, intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2