Papers
3
Total Citations
39
H-Index
3
About
Haowen Pan is a researcher at the intersection of robotics, agricultural automation, and wireless power transfer systems. His work primarily focuses on developing intelligent robotic solutions for precision agriculture and optimizing energy delivery to Internet of Things (IoT) devices. Pan’s most impactful contribution is his 2022 paper on identifying the operating position and orientation of a robotic kiwifruit pollinator, which has garnered 27 citations—a strong indicator of its relevance to the growing field of agricultural robotics. In parallel, he has pioneered the use of deep reinforcement learning for path planning in mobile wireless power transfer systems, as demonstrated in his 2022 study on area division deep reinforcement learning (9 citations). This work addresses the critical challenge of efficiently charging IoT devices using a mobile RF transmitter mounted on a robot. Further extending this line of inquiry, Pan has also explored finite state machine reinforcement learning to optimize mobile wireless power transfer (3 citations). His research is notable for bridging practical agricultural needs with cutting-edge AI-driven optimization, offering scalable solutions for both crop pollination and sustainable IoT energy management.
Research Focus
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