Papers
4
Total Citations
31
H-Index
4
About
Samuel Cheong is a roboticist advancing the frontier of mobile manipulation, with a focus on hybrid wheeled-legged robots that can seamlessly transition between locomotion and dexterous tasks. His core research spans state estimation, supervised autonomy, and human-robot collaboration, with significant contributions to enabling robots to operate in unstructured, real-world environments. Cheong’s most cited work introduces a novel state estimation framework that fuses multiple sensors to maintain robust tracking during hybrid locomotion, a critical advancement for robots performing mobile manipulation tasks. He has also pioneered a framework for tool cognition that allows robots to use tools without prior learning or observation, opening new possibilities for autonomous adaptation. His work on supervised autonomy for remote teleoperation of quadrupedal bimanual manipulators has improved operator efficiency in unknown environments, while his system-of-systems approach to human-robot collaboration has enhanced task performance in search and rescue operations. With over 30 citations across his key publications, Cheong’s research is shaping the next generation of mobile manipulators that can work alongside humans in dynamic, high-stakes settings.
Research Focus
Key Achievements
Top Papers
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