Zhaokui Wang
Papers
4
Total Citations
29
H-Index
3
About
Dr. Zhaokui Wang is a leading researcher in space robotics and human-robot interaction, specializing in intelligent systems for extraterrestrial and orbital environments. His work focuses on enabling autonomous robots to assist astronauts in challenging settings, from space stations to the lunar surface. Wang’s major contributions include developing a deep learning and probabilistic model for real-time astronaut visual tracking, allowing flying assistant robots to follow and aid crew members in the International Space Station—a foundational paper with 14 citations. He also pioneered dual-arm control for lunar assisted robots using hierarchical reinforcement learning, enabling automatic trajectory planning in unstructured lunar terrains (7 citations). Further, Wang advanced human-robot interaction by predicting human intentions from single actions via convolutional neural networks, moving beyond rigid instruction-following (5 citations). His research on deep reinforcement learning for obstacle avoidance in lunar robots, integrating data fusion for uncertain environments, has garnered 3 citations. Collectively, Wang’s work bridges artificial intelligence and space exploration, enhancing robot autonomy and safety in extreme conditions. His achievements underscore a commitment to making robotic assistants intuitive, adaptive, and reliable partners for astronauts, with potential applications in future lunar bases and deep-space missions.
Research Focus
Key Achievements
Top Papers
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