Bukun Son
Papers
3
Total Citations
54
H-Index
3
About
Bukun Son is a robotics researcher whose work centers on autonomous systems, robotic manipulation, and locomotion control. His most significant contribution is in autonomous excavation, where he developed an "Expert-Emulating Excavation Trajectory Planning" framework for industrial robotic excavators. This novel approach mimics the strategies of human operators to optimize digging in complex, unmodellable soils while prioritizing robustness and safety—a critical advancement for construction and mining automation, earning 30 citations. Son has also made impactful contributions to robot simulation, authoring a "Comparative Study of Physics Engines for Robot Simulation with Mechanical Interaction" (20 citations), which provides essential guidance for selecting simulation tools for developing control algorithms quickly and safely. Additionally, his work on "Learning multiple gaits of quadruped robot using hierarchical reinforcement learning" addresses the limitation of single-gait policies in velocity command tracking, enabling more adaptive and efficient locomotion. Through these studies, Son demonstrates a clear focus on bridging the gap between human expertise and autonomous robotic performance, with his research directly informing safer, more capable industrial and legged robots.
Research Focus
Key Achievements
Top Papers
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