Max Robotics — Global Service Robot Directory + US Certification

About

Fengwei An is a researcher specializing in hardware architecture design, computer vision, and embedded intelligence for autonomous and mobile robotic systems. His work sits at the intersection of FPGA-based accelerator design and machine learning, with a particular focus on enabling real-time visual perception under stringent power and area constraints typical of edge computing environments. An's most significant contributions involve the design of dedicated coprocessors for object detection and classification. His dual-feature-space architectures, which combine Histogram of Oriented Gradient (HOG) and Local Binary Pattern (LBP) descriptors with classifiers such as SVM and weighted Softmax, have demonstrated practical pathways for deploying multi-class detection on resource-limited hardware. These papers have each accumulated 14 citations, reflecting steady influence within the embedded vision community. His FPGA-based object detection processor and reconfigurable matrix multiplication coprocessor — each garnering 11 citations — further underscore his commitment to area-efficient and energy-efficient designs applicable to intelligent robots. Beyond object detection, An has contributed to robot navigation through pseudo-binocular stereo vision, visual-inertial odometry acceleration, and efficient edge detection hardware. Collectively, his body of work advances the feasibility of deploying sophisticated autonomous perception directly onto mobile and wearable platforms.