Haopeng Zhao

Papers

Total Citations

H-Index

About

Haopeng Zhao is an emerging researcher specializing in autonomous systems, robotics, and intelligent navigation, with a particular focus on applying advanced computational algorithms to real-world mobility challenges. His work sits at the intersection of machine learning, path planning, and unmanned vehicle systems, addressing some of the most pressing challenges in modern robotics and logistics automation. Zhao's most notable contribution to date is his 2024 paper on autonomous navigation of unmanned vehicles through Deep Reinforcement Learning, which has already garnered 14 citations. This work advances the application of the Deep Deterministic Policy Gradient algorithm to tackle high-dimensional, continuous action spaces — a significant technical hurdle in autonomous vehicle development. Building on this foundation, his 2025 research on optimized path planning for logistics robots introduces an enhanced Ant Colony Algorithm capable of handling complex multi-constraint environments, including time windows and motion smoothness requirements, accumulating 8 citations since publication. Together, these contributions reflect Zhao's commitment to bridging theoretical AI methodologies with practical deployment challenges in autonomous systems. His growing citation record suggests increasing recognition within the robotics and intelligent transportation communities, positioning him as a promising voice in next-generation autonomous mobility research.