Papers

4

Total Citations

25

H-Index

3

About

Lejun Wang is a robotics and control systems researcher whose work centers on the challenging domain of underactuated robotic systems, with a particular focus on developing innovative control strategies for planar and swarm robotic platforms. Wang's research addresses one of the fundamental difficulties in robotics: achieving stable, precise control in systems where the number of control inputs is fewer than the degrees of freedom, a constraint that demands sophisticated mathematical and algorithmic solutions. Wang's most significant contributions include pioneering finite-time control strategies for swarm planar underactuated robots, combining motion planning with intelligent algorithms to enable coordinated multi-robot task completion efficiently and with minimal energy expenditure. This work, his most cited with 12 citations, demonstrates practical promise for lightweight, gravity-independent robotic systems. Further contributions include a generalizable control method for R-type underactuated manipulators capable of handling diverse initial conditions, including nonzero velocity states, and an iterative contraction stability strategy for prismatic-rotational underactuated configurations grounded in nilpotent approximation theory. Across his growing publication record, Wang consistently bridges theoretical control mathematics with intelligent optimization techniques, establishing a coherent research identity focused on making underactuated robotics more reliable and broadly applicable in real-world engineering contexts.

Research Focus

Key Achievements

3
H-Index
4
Papers
25
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Finite-time control strategy for swarm planar underactuated robots via motion planning and intelligent algorithm
12 citations · 2022
📈 Most Prolific Year: 2023 (3 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Chongqing University of Posts and Telecommunications

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago