Amitabha Ghosh
Papers
8
Total Citations
294
H-Index
6
About
Amitabha Ghosh is a pioneering researcher in the fields of robotics, artificial intelligence, and autonomous systems, whose work has significantly advanced the application of hybrid computational intelligence techniques to complex robot navigation and motion planning challenges. Throughout his career, Ghosh has championed the integration of fuzzy logic and genetic algorithms — a "genetic-fuzzy" paradigm — to tackle problems that traditional methods struggle to solve efficiently. His most influential contribution, a 1999 paper on mobile robot navigation among moving obstacles, has garnered over 133 citations and established a foundational framework for adaptive, real-time obstacle avoidance. Ghosh extended this expertise to legged robotics, developing sophisticated gait generation and path planning systems for six-legged robots, with his 2002 work on simultaneous path and gait optimization earning 62 citations. His earlier research in 1993 laid important groundwork by addressing optimum path planning for robot manipulators in environments with both static and dynamic obstacles. Across his portfolio, Ghosh consistently transformed computationally expensive robotics problems into tractable ones through elegant hybrid AI solutions, earning him a respected place in the autonomous robotics research community.
Research Focus
Key Achievements
Top Papers
- 1A genetic-fuzzy approach for mobile robot navigation among moving obstacles133 citations · 1999
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- 5Optimal turning gait of a six-legged robot using a GA-fuzzy approach20 citations · 2000
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