Yulu Wang

Wuhan University of Technology, Qingdao University of Technology

Papers

Total Citations

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About

Yulu Wang’s research centers on embedded systems, autonomous driving, and mobile robotics, with a particular focus on hardware acceleration and intelligent path planning. In their 2023 work, Wang developed an FPGA-based hardware system for real-time target recognition and sorting, designed to meet the stringent speed and power constraints of autonomous driving. This low-cost, low-consumption approach has garnered 3 citations, highlighting its relevance in efficient edge computing. Complementing this, Wang’s 2019 study introduced a novel global path planning method for mobile robots using the beetle antennae search (BAS) algorithm, which significantly improved obstacle avoidance and adaptability by optimizing the distance-to-target fitness function. This work, also with 3 citations, demonstrates Wang’s ability to bridge bio-inspired computation with practical robotics. Together, these contributions showcase Wang’s commitment to advancing real-time, resource-efficient systems for autonomous navigation, offering valuable insights for researchers in hardware-software co-design and intelligent control.