Jie Wang
Papers
1
Total Citations
16
H-Index
1
About
Jie Wang is a robotics and autonomous systems researcher whose work centers on intelligent motion planning, navigation, and control of mobile robots. Wang's most recognized contribution lies in the development of an Improved Artificial Potential Field (IAPF) algorithm for mobile robot path planning, addressing longstanding limitations of classical approaches — including inefficiency, local optimization traps, and target unreachability in unknown environments. Published in 2022 and already accumulating 16 citations, this work represents a meaningful advancement in how autonomous robots navigate complex, dynamic surroundings. By reformulating the foundational potential field model, Wang's research offers more robust and reliable obstacle avoidance strategies that have clear implications for real-world robotic deployment in areas such as warehouse automation, search and rescue, and autonomous vehicles. The rapid uptake of this research within the community signals its practical relevance and methodological novelty. Wang's contributions reflect a broader commitment to bridging theoretical algorithmic design with applied robotics challenges, making their work particularly valuable for students and engineers seeking effective solutions to autonomous navigation problems in unstructured environments.
Research Focus
Key Achievements
Top Papers
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