Fengde Xu
Papers
2
Total Citations
4
H-Index
1
About
Fengde Xu is a pioneering roboticist whose work centers on the design and intelligent control of novel spherical multi-limbed robots, with a particular focus on expanding the locomotion capabilities of machines in complex, unstructured environments. His research integrates physics-based modeling with advanced artificial intelligence, specifically deep reinforcement learning, to solve critical challenges in motion planning. Xu’s most notable contribution is the development of a physics-driven, closed-loop motion planning method for spherical multi-expandable-limb robots, a platform uniquely capable of omnidirectional movement, wide deformation, and robust radial force output. This work, published in 2024, has already garnered 3 citations for its direct applicability to disaster relief, combat reconnaissance, and cave exploration. In his 2025 study, Xu advanced the field further by applying deep reinforcement learning to achieve adaptive leg motion for spherical multi-retractable legged robots, addressing a critical gap in individual leg dynamics analysis. By bridging the gap between theoretical mechanics and data-driven control, Xu is establishing a new paradigm for versatile, all-terrain robotic systems, positioning him as a rising leader in the field of mobile robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2