Zhaoyi Zhang

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About

Zhaoyi Zhang is a researcher advancing the field of autonomous navigation and intelligent robotics, with a primary focus on path planning and reinforcement learning. Their most notable contribution, "An Algorithm of Complete Coverage Path Planning Based on Improved DQN" (2023), introduces a novel approach that enhances the Deep Q-Network (DQN) framework to achieve efficient and thorough area coverage for mobile robots. This work addresses a critical challenge in autonomous systems—ensuring complete coverage without redundant paths—by integrating improved exploration strategies and reward shaping. While still early in its impact, with 2 citations, the paper demonstrates Zhang’s ability to bridge theoretical reinforcement learning with practical robotic applications. Their research holds promise for real-world uses in automated cleaning, agricultural surveying, and search-and-rescue operations. Zhang’s work reflects a commitment to solving complex spatial planning problems, positioning them as an emerging voice in the intersection of machine learning and robotics. As their citation footprint grows, their algorithmic innovations are likely to influence future studies in coverage path planning and adaptive control systems.