Papers
13
Total Citations
216
H-Index
10
About
Xingkun Liu is a pioneering researcher at the intersection of robotics, human-robot interaction, and bioinspired design, with a career spanning autonomous systems, conversational agents, and robotic locomotion. His most influential work, "A Digital Twin for Human-Robot Interaction" (56 citations), addresses critical safety needs in the energy industry by developing a unified simulation framework for autonomous robots—including Husky, ANYmal, and UAVs—enabling remote facility maintenance without human risk. Liu has made significant contributions to search and rescue robotics, notably through his leadership in the euRathlon 2015 multi-domain grand challenge (29 citations), which advanced multi-robot coordination in disaster scenarios. His bioinspired robotics research is equally impactful, including the kinematic synthesis of a locust-inspired jumping leg mechanism (22 citations) and dynamic stability analysis for bipedal lateral jumping in rugged terrain (17 citations). Liu is also a key figure in explainable AI, developing natural language interfaces that allow users to query autonomous robot behavior (18 citations), enhancing transparency and trust. His work on trustworthy embodiment for conversational agents (13 citations) explores how physical robots can improve human-robot teaming in remote environments. With over 200 total citations across these diverse areas, Liu’s research is shaping the future of safe, explainable, and agile autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1A Digital Twin for Human-Robot Interaction56 citations · 2019
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- 9Towards a Conversational Agent for Remote Robot-Human Teaming11 citations · 2019
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