Qun Lin

Curtin University

Papers

2

Total Citations

7

H-Index

2

About

Qun Lin is a researcher whose work lies at the intersection of nonlinear control theory and robotic path planning, with a focus on achieving precise, efficient motion for complex systems. A key contribution is the development of a novel method to minimize control volatility in nonlinear systems, employing smooth piecewise-quadratic input signals to reduce actuator wear and energy consumption (2020, 4 citations). This work addresses a critical challenge in real-world control applications where abrupt signal changes can degrade performance. Earlier, Lin made significant strides in micro-robotics by devising an optimal path planning strategy for underactuated Dubins micro-robots—non-holonomic agents constrained to circular arcs of fixed curvature (2013, 3 citations). This research tackled the fundamental coverage and optimal path problems for these tiny, maneuverability-limited robots, enabling more reliable navigation in constrained environments. While still early in their career, Lin’s contributions demonstrate a clear ability to solve practical, mathematically rigorous problems in control and robotics, laying a strong foundation for future impact in autonomous systems and precision motion control.

Research Focus

Key Achievements

2
H-Index
2
Papers
7
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Minimizing control volatility for nonlinear systems with smooth piecewise-quadratic input signals
4 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Curtin University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago