Anjan Rakshit
Papers
21
Total Citations
315
H-Index
10
About
Anjan Rakshit is a prominent researcher specializing in autonomous mobile robotics, human-robot coexistence, and intelligent control systems, with particular expertise in vision-based sensing, robot navigation, and sensor fusion. His work has made substantial contributions to the field of adaptive control, combining computational intelligence techniques with rigorous mathematical frameworks to enable robots to navigate and interact safely in real-world environments. Rakshit's most celebrated contribution, a PSO-Lyapunov hybrid stable adaptive fuzzy tracking control approach for vision-based robot navigation (2012, 57 citations), elegantly merges particle swarm optimization with Lyapunov stability theory to deliver reliable autonomous navigation. His broader navigation research, including multi-layered subgoal algorithms and harmony search-based controllers, established robust foundations for mobile robot path planning. A significant thread of his work addresses the challenge of human detection and tracking in human-robot coexisting environments, where he pioneered vision sensor-based shoe detection methodologies employing clustering algorithms such as DBSCAN and OPTICS, as well as chaos-based random sampling techniques. More recently, his research has advanced toward sophisticated sensor fusion using heteroscedastic Gaussian process regression and sonar scan matching for extended target tracking. With over 250 cumulative citations, Rakshit's interdisciplinary contributions continue to meaningfully shape the landscape of intelligent robotics and human-aware autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 4Vision Based Autonomous Robot Navigation26 citations · 2012
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