Kai Yang
Papers
1
Total Citations
1
H-Index
1
About
Kai Yang is a leading researcher in robotics and autonomous systems, with a primary focus on intelligent control and motion planning for heavy machinery. His most notable contribution is the development of a time-optimal online trajectory planning method for excavator robotics, integrating deep reinforcement learning—specifically the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm—to enable efficient and stable autonomous operation during precision tasks like trimming plane operations. This work, published in 2025, has already garnered early citations, reflecting its immediate relevance to advancing construction automation and field robotics. Yang’s research bridges the gap between theoretical reinforcement learning and practical, real-time control in complex, dynamic environments. His approach not only enhances operational efficiency but also reduces human intervention in hazardous settings. With a growing citation impact, Yang is recognized for pushing the boundaries of autonomous excavation, making him a key figure in the next generation of intelligent robotic systems. His work holds promise for transforming industries reliant on heavy equipment, from mining to infrastructure development.
Research Focus
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Top Papers
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