Jianfei Cao

Papers

Total Citations

H-Index

About

Jianfei Cao is a researcher at the forefront of embedded robotics and real-time perception, specializing in visual simultaneous localization and mapping (SLAM) and 3D mapping on resource-constrained platforms. His work bridges the gap between advanced computer vision algorithms and efficient hardware implementation, particularly on Field-Programmable Gate Arrays (FPGAs). Cao’s most cited paper, “CNN-based Monocular Decentralized SLAM on embedded FPGA” (2020, 9 citations), introduces a decentralized visual SLAM system that enables multiple robots to collaboratively estimate their 6-DoF poses and share environmental information—a critical capability for multi-robot applications like search-and-rescue or warehouse automation. In his follow-up work, “GAME: Gaussian Mixture Model Mapping and Navigation Engine on Embedded FPGA” (2021, 3 citations), he tackles the challenge of 3D mapping by replacing traditional discrete spatial representations with a continuous Gaussian Mixture Model, drastically reducing memory requirements while improving representation fidelity. By demonstrating that complex probabilistic models can run efficiently on embedded FPGAs, Cao is paving the way for smarter, more autonomous robots that operate without reliance on cloud computing. His contributions are particularly impactful for students and engineers seeking to deploy AI-driven robotics in real-world, low-power environments.