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About

Di Fan is a robotics researcher whose work centers on bio-inspired vision systems, robotic manipulation, and multi-agent energy optimization. His most impactful contribution is in the development of anthropomorphic robotic bionic eyes, where he pioneered a compact serial mechanism design that includes a crucial eye roll degree of freedom—enabling image stabilization and more natural gaze control. His 2020 paper on eye gaze based 3D triangulation (11 citations) advances active binocular vision by solving the challenge of online stereo calibration for non-fixed cameras, a key step toward more lifelike robotic vision. Fan also addresses practical energy efficiency in robotics: his work on optimizing formation control for multiple robotic fishes using particle swarm optimization (4 citations) and his energy-aware planning approach for a seven-DOF robotic arm grasping moving bottles (2 citations) demonstrate a consistent focus on reducing power consumption without sacrificing performance. With a total of 25 citations across his most cited works, Fan’s research sits at the intersection of biomimetic design, computer vision, and sustainable robotics—offering tangible pathways for more agile, efficient, and human-like robotic systems.