Animesh Chhotray
Papers
14
Total Citations
156
H-Index
9
About
Animesh Chhotray is a robotics researcher whose work sits at the intersection of intelligent control, path planning, and autonomous navigation for mobile and humanoid robots. His primary contributions focus on developing novel algorithms that enable robots to navigate complex, unknown, and obstacle-cluttered environments with greater stability and efficiency. Chhotray is perhaps best known for his work on the DAYANI arc contour intelligent technique and its integration with back-propagation neural networks, a method he applied to the challenging problem of two-wheeled self-balancing robot navigation. He has also made significant strides in humanoid robotics, proposing a hybridized RA-APSO approach for humanoid navigation and a 3D-LIPM-based gait planning strategy for the NAO robot. His research portfolio, which includes over a dozen papers with key works accumulating 15-20 citations each, demonstrates a sustained focus on merging classical control theory with soft computing techniques like fuzzy logic, tabu search, and glowworm swarm optimization. Chhotray’s work is particularly notable for its practical, real-time applicability, offering robust solutions for dynamic path planning in both static and dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Controlled Gait Planning of Humanoid Robot NAO Based on 3D-LIPM Model19 citations · 2020
- 3A hybridized RA-APSO approach for humanoid navigation18 citations · 2017
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- 7Path Planning of a Humanoid Robot Using Rule-Based Technique11 citations · 2020
- 8
- 9Kinematic Analysis of a Two-Wheeled Self-Balancing Mobile Robot9 citations · 2016
- 10