Nirangkush Das
Papers
3
Total Citations
19
H-Index
3
About
Nirangkush Das is a robotics and control systems researcher whose work focuses on autonomous ground vehicle navigation, trajectory tracking, and multi-robot coordination. His research addresses fundamental challenges in mobile robotics by developing practical, cost-effective solutions that bridge theoretical control frameworks with real-world implementation. Das is perhaps best known for his 2019 study comparing kinematic and dynamic model-based linear Model Predictive Control (MPC) for non-holonomic robot trajectory tracking, which has garnered 10 citations and introduced an innovative hierarchical inner-outer control structure pairing MPC with a PI controller — a contribution that directly addresses critical performance trade-offs in autonomous navigation. Complementing this work, his two-part series on modeling, design, and control of low-cost differential-drive robotic ground vehicles (2017, earning 5 and 4 citations respectively) tackles the ambitious challenge of building fleets of cooperating autonomous machines, demonstrating how off-the-shelf hardware can be leveraged effectively for sophisticated multi-robot coordination within the FAME (Flexible Autonomous Machines operating in an uncertain Environment) framework. Together, these contributions reflect Das's commitment to making autonomous robotics more accessible and scalable, offering valuable insights for researchers and engineers working on affordable, deployable robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3