Papers
7
Total Citations
119
H-Index
6
About
Jian Wan is a robotics researcher whose work spans autonomous systems, human-robot interaction, and control theory. His most impactful contributions focus on enabling robots to operate in dynamic, real-world environments. He pioneered methods for autonomous UAV landing on moving vessels using fiducial markers (35 citations), solving a critical challenge for maritime robotics. Wan also advanced teleoperation and teaching-by-demonstration systems, fusing data from Kinect sensors and MYO armbands with Kalman filters to control Baxter and Nao robots (29 and 20 citations respectively). His work on neural learning and sensor fusion for robot programming (13 citations) further demonstrates his expertise in making robots more accessible and intuitive to control. Earlier in his career, Wan contributed to predictive control theory, developing computationally reliable contractive MPC approaches for discrete-time systems (10 citations) and applying predictive motion control to mobile robots (8 citations). His research has practical applications in autonomous sailing as well, with experimental studies on radio-controlled sailboats (4 citations). With over 100 total citations across his most-cited works, Wan's research bridges theoretical control methods and practical robotic systems, making significant contributions to autonomous navigation, human-robot collaboration, and sensor fusion technologies.
Research Focus
Key Achievements
Top Papers
- 1Towards autonomous landing on a moving vessel through fiducial markers35 citations · 2017
- 2
- 3Development of Kinect based teleoperation of Nao robot20 citations · 2016
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- 6Predictive motion control of a mirosot mobile robot8 citations · 2004
- 7