Fengzhi Guo
Papers
5
Total Citations
17
H-Index
3
About
Fengzhi Guo is a robotics researcher specializing in pretouch sensing for robotic grasping and manipulation. His work focuses on developing novel fingertip-mounted sensors that enable robots to perceive object properties—including distance, material type, and interior structure—without making physical contact. Guo’s key contributions include the design of Dual-Modal and Dual Sensing Mechanisms (DMDSM) sensors, which combine pulse-echo ultrasound and optoacoustics to achieve near-distance ranging and material detection. He has advanced this technology through multiple generations, from the original DMDSM sensor to the third-generation (G3) and full-optical PDM² sensors, each iteration improving sensing accuracy and integration. His material and structure mapping (MSM) algorithm further enhances robotic grasp planning by translating sensor data into actionable object models. Though early in his career, Guo’s work has already garnered citations across his publications, with his 2022 paper on object scanning systems receiving the most attention. His research bridges sensor hardware development and perception algorithms, offering practical solutions for autonomous robotic systems in unstructured environments.
Research Focus
Key Achievements
Top Papers
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