Papers
16
Total Citations
296
H-Index
9
About
Nirmal Baran Hui is a robotics and autonomous systems researcher whose work has made significant contributions to mobile robot navigation, path planning, and multi-robot coordination. His research spans intelligent control systems, neuro-fuzzy methods, and evolutionary computation, with a particular focus on enabling robots to navigate complex, dynamic environments efficiently and safely. Hui's most influential work, "Time-optimal, collision-free navigation of a car-like mobile robot using neuro-fuzzy approaches" (2006), has garnered 99 citations and established him as a leading voice in intelligent robot motion planning. His early research demonstrated how genetic algorithms could automate the design of fuzzy logic controllers for collision avoidance—a computationally elegant solution to a notoriously difficult problem. A comparative study on real-robot navigation in dynamic environments (2009, 60 citations) further cemented his reputation for bridging theoretical methods with practical implementation. More recently, Hui has tackled the challenges of multi-robot systems, exploring hybrid neural network approaches and potential field methods for coordinated motion planning, earning continued recognition from the research community. His work on all-terrain robot development also reflects a commitment to real-world robotic applications. With over 250 cumulative citations, Hui's career represents a sustained and evolving contribution to intelligent autonomous robotics.
Research Focus
Key Achievements
Top Papers
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- 4Camera calibration using a genetic algorithm13 citations · 2008
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- 6Multi-agent Navigation and Coordination Using GA-Fuzzy Approach11 citations · 2018
- 7Design and development of an automated all-terrain wheeled robot10 citations · 2014
- 8Intelligent navigation of multiple coordinated robots10 citations · 2019
- 9
- 10Motion planning and coordination of multi-agent systems9 citations · 2018